This function computes three RIPD statistics–\(RIPD_{R}\), \(RIPD_{S}\), and \(RIPD_{RS}\)–for each item. \(RIPD_{R}\) captures differences in mean raw residuals between groups, which is typically indicative of uniform item parameter drift (IPD). \(RIPD_{S}\) captures differences in mean squared residuals between groups, reflecting nonuniform IPD. \(RIPD_{RS}\), a combined chi-square-based index, is sensitive to both uniform and nonuniform IPD.
Usage
ripd(x, ...)
# Default S3 method
ripd(
x,
data,
score = NULL,
group,
focal.name,
item.skip = NULL,
D = 1,
alpha = 0.05,
missing = NA,
purify = FALSE,
purify.by = c("ripdrs", "ripdr", "ripds"),
max.iter = 10,
min.resp = NULL,
method = "ML",
range = c(-5, 5),
norm.prior = c(0, 1),
nquad = 41,
weights = NULL,
ncore = 1,
verbose = TRUE,
...
)
# S3 method for class 'est_irt'
ripd(
x,
score = NULL,
group,
focal.name,
item.skip = NULL,
alpha = 0.05,
missing = NA,
purify = FALSE,
purify.by = c("ripdrs", "ripdr", "ripds"),
max.iter = 10,
min.resp = NULL,
method = "ML",
range = c(-5, 5),
norm.prior = c(0, 1),
nquad = 41,
weights = NULL,
ncore = 1,
verbose = TRUE,
...
)
# S3 method for class 'est_item'
ripd(
x,
group,
focal.name,
item.skip = NULL,
alpha = 0.05,
missing = NA,
purify = FALSE,
purify.by = c("ripdrs", "ripdr", "ripds"),
max.iter = 10,
min.resp = NULL,
method = "ML",
range = c(-5, 5),
norm.prior = c(0, 1),
nquad = 41,
weights = NULL,
ncore = 1,
verbose = TRUE,
...
)Arguments
- x
A data frame containing item metadata (e.g., item parameters, number of categories, IRT model types, etc.); or an object of class
est_irtobtained fromest_irt(), orest_itemfromest_item().See
est_irt()orsimdat()for more details about the item metadata. This data frame can be easily created using theshape_df()function.- ...
Additional arguments passed to the
est_score()function.- data
A matrix of examinees' item responses corresponding to the items specified in the
xargument. Rows represent examinees and columns represent items.- score
A numeric vector containing examinees' ability estimates (theta values). If not provided,
ripd()will estimate ability parameters internally before computing the RIPD statistics. Seeest_score()for more information on scoring methods. Default isNULL.- group
A numeric or character vector indicating group membership of examinees. The length of the vector should be the same as the number of rows in the response data matrix.
- focal.name
A single numeric or character value specifying the focal group. For instance, given
group = c(0, 1, 0, 1, 1)and '1' indicating the focal group, setfocal.name = 1.- item.skip
A numeric vector of item indices to exclude from IPD analysis. If NULL, all items are included. Useful for omitting specific items based on prior insights.
- D
A scaling constant used in IRT models to make the logistic function closely approximate the normal ogive function. A value of 1.7 is commonly used for this purpose. Default is 1.
- alpha
A numeric value specifying the significance level (\(\alpha\)) for hypothesis testing using the RIPD statistics. Default is
0.05.- missing
A value indicating missing values in the response data set. Default is NA.
- purify
Logical. Indicates whether to apply a purification procedure. Default is
FALSE.- purify.by
A character string specifying which RIPD statistic is used to perform the purification. Available options are "ripdrs" for \(RIPD_{RS}\), "ripdr" for \(RIPD_{R}\), and "ripds" for \(RIPD_{S}\).
- max.iter
A positive integer specifying the maximum number of iterations allowed for the purification process. Default is
10.- min.resp
A positive integer specifying the minimum number of valid item responses required from an examinee in order to compute an ability estimate. Default is
NULL.- method
A character string indicating the scoring method to use. Available options are:
"ML": Maximum likelihood estimation"WL": Weighted likelihood estimation (Warm, 1989)"MAP": Maximum a posteriori estimation (Hambleton et al., 1991)"EAP": Expected a posteriori estimation (Bock & Mislevy, 1982)
Default is
"ML".- range
A numeric vector of length two specifying the lower and upper bounds of the ability scale. This is used for the following scoring methods:
"ML","WL", and"MAP". Default isc(-5, 5).- norm.prior
A numeric vector of length two specifying the mean and standard deviation of the normal prior distribution. These values are used to generate the Gaussian quadrature points and weights. Ignored if
methodis"ML"or"WL". Default isc(0, 1).- nquad
An integer indicating the number of Gaussian quadrature points to be generated from the normal prior distribution. Used only when
methodis"EAP". Ignored for"ML","WL", and"MAP". Default is 41.- weights
A two-column matrix or data frame containing the quadrature points (in the first column) and their corresponding weights (in the second column) for the latent variable prior distribution. The weights and points can be conveniently generated using the function
gen.weight().If
NULLandmethod = "EAP", default quadrature values are generated based on thenorm.priorandnquadarguments. Ignored ifmethodis"ML","WL", or"MAP".- ncore
An integer specifying the number of logical CPU cores to use for parallel processing. Default is
1. Seeest_score()for details.- verbose
Logical. If
TRUE, progress messages from the purification procedure will be displayed; ifFALSE, the messages will be suppressed. Default isTRUE.
Value
This function returns a list containing four main components:
- no_purify
A list of sub-objects containing the results of IPD analysis without applying a purification procedure. The sub-objects include:
- ipd_stat
A data frame summarizing the RIPD analysis results for all items. The columns include: item ID, \(RIPD_{R}\) statistic, standardized \(RIPD_{R}\), \(RIPD_{S}\) statistic, standardized \(RIPD_{S}\), \(RIPD_{RS}\) statistic, p-values for \(RIPD_{R}\), \(RIPD_{S}\), and \(RIPD_{RS}\), sample sizes for the reference and focal groups, and total sample size. Note that \(RIPD_{RS}\) does not have a standardized value because it is a \(\chi^{2}\)-based statistic.
- moments
A data frame reporting the first and second moments of the RIPD statistics. The columns include: item ID, mean and standard deviation of \(RIPD_{R}\), mean and standard deviation of \(RIPD_{S}\), and the covariance between \(RIPD_{R}\) and \(RIPD_{S}\).
- ipd_item
A list of three numeric vectors identifying items flagged as drifting by each RIPD statistic: \(RIPD_{R}\), \(RIPD_{S}\), and \(RIPD_{RS}\).
- score
A numeric vector of ability estimates used to compute the RIPD statistics.
- purify
A logical value indicating whether the purification procedure was applied.
- with_purify
A list of sub-objects containing the results of IPD analysis with a purification procedure. The sub-objects include:
- purify.by
A character string indicating the RIPD statistic used for purification. Possible values are "ripdr", "ripds", and "ripdrs", corresponding to \(RIPD_{R}\), \(RIPD_{S}\), and \(RIPD_{RS}\), respectively.
- ipd_stat
A data frame reporting the RIPD analysis results for all items from the final iteration. Same structure as in
no_purify, with one additional column indicating the iteration number in which each result was obtained.- moments
A data frame reporting the moments of RIPD statistics from the final iteration. Includes the same columns as in
no_purify, with an additional column for the iteration number.- ipd_item
A numeric vector of item indices (row positions in
x) identified as IPD items across all purification iterations, sorted in ascending order.- n.iter
An integer indicating the total number of iterations performed during the purification process.
- score
A numeric vector of purified ability estimates used to compute the final RIPD statistics.
- complete
A logical value indicating whether the purification process converged. If
FALSE, the maximum number of iterations was reached without convergence.
- alpha
A numeric value indicating the significance level (\(\alpha\)) used in hypothesis testing for RIPD statistics.
Details
Theoretical Background: From RDIF to RIPD
The RIPD framework directly adapts the residual-based differential item functioning (RDIF) detection framework (Lim et al., 2022; Lim & Choe, 2023) to detect item parameter drift (IPD) in computerized adaptive testing (CAT). Each RIPD statistic (\(RIPD_R\), \(RIPD_S\), \(RIPD_{RS}\)) mirrors its RDIF counterpart (\(RDIF_R\), \(RDIF_S\), \(RDIF_{RS}\)) in both computation and asymptotic theory, with one key adaptation: whereas the original RDIF framework estimates item parameters once from the pooled data of both groups, the RIPD framework uses the original, pre-calibrated item parameters from the CAT pool directly, eliminating the need for item recalibration. This makes RIPD practically scalable for operational CAT programs where recalibration is often infeasible due to sparse and non-ignorably missing response data.
IPD in CAT can be viewed as a special case of DIF across time (Lord, 1980; Veerkamp & Glas, 2000): the focal group represents current test-takers whose responses may reflect drift, while the reference group represents a baseline under invariant item parameters.
Residual Definition
For examinee \(i\) and item \(j\), the raw residual is defined as $$e_{ij} = u_{ij} - P_j(\hat{\theta}_i),$$ where \(u_{ij}\) is the observed binary response (0 or 1) and \(P_j(\hat{\theta}_i)\) is the model-predicted probability of a correct response under the original item parameters evaluated at the examinee's ability estimate \(\hat{\theta}_i\). Because item responses are independent but not identically distributed (due to varying predicted probabilities across examinees with different ability levels), the asymptotic distributions of the RIPD statistics are established via Lyapunov's central limit theorem.
Three RIPD Statistics and Their Asymptotic Distributions
RIPD\(_R\) (uniform drift): Measures the difference in mean raw residuals between the focal (\(F\)) and reference (\(R\)) groups, $$RIPD_{R,j} = \frac{\sum_{i \in F} e_{ij}}{N_F} - \frac{\sum_{i \in R} e_{ij}}{N_R}.$$ \(RIPD_{R,j}\) is most effective when the item response functions (IRFs) of the two groups differ primarily in location (e.g., drift in the difficulty \(b\) or guessing \(c\) parameter). Under the null hypothesis \(H_0\) of no IPD, \(RIPD_{R,j}\) asymptotically follows a normal distribution with mean zero and analytically derived variance \(\sigma^2_{RIPD_R} = \frac{\sum_{i \in F} P_{ij}(1 - P_{ij})}{N_F^2} + \frac{\sum_{i \in R} P_{ij}(1 - P_{ij})}{N_R^2}\). A standard Z-test is then applied as \(Z_R = RIPD_{R,j} / \sigma_{RIPD_R}\).
RIPD\(_S\) (nonuniform drift): Measures the difference in mean squared residuals between groups, $$RIPD_{S,j} = \frac{\sum_{i \in F} e_{ij}^2}{N_F} - \frac{\sum_{i \in R} e_{ij}^2}{N_R}.$$ \(RIPD_{S,j}\) captures drift that varies across the ability continuum, such as a change in the discrimination parameter \(a\), which \(RIPD_{R,j}\) alone may not detect. Importantly, under \(H_0\), the null mean of \(RIPD_{S,j}\) is not zero in general; it equals $$\mu_{RIPD_S} = \frac{\sum_{i \in F} P_{ij}(1 - P_{ij})}{N_F} - \frac{\sum_{i \in R} P_{ij}(1 - P_{ij})}{N_R},$$ which is a function of the predicted probabilities in both groups and vanishes only when their ability distributions are perfectly matched (as in the RIPD setup where focal \(\hat{\theta}\) values are reused for the synthetic reference group). The asymptotic variance is also analytically derived. A standard Z-test is applied as \(Z_S = (RIPD_{S,j} - \mu_{RIPD_S}) / \sigma_{RIPD_S}\).
RIPD\(_{RS}\) (combined): A Wald-type statistic that jointly tests for uniform and nonuniform drift within a single framework, $$RIPD_{RS,j} = (\boldsymbol{\nu}_j - \boldsymbol{\mu}_j)^\top \hat{\boldsymbol{\Sigma}}_j^{-1} (\boldsymbol{\nu}_j - \boldsymbol{\mu}_j),$$ where \(\boldsymbol{\nu}_j = (RIPD_{R,j},\ RIPD_{S,j})^\top\), \(\boldsymbol{\mu}_j = (\mu_{RIPD_R},\ \mu_{RIPD_S})^\top\) is the vector of null means, and \(\hat{\boldsymbol{\Sigma}}_j\) is the analytically derived \(2 \times 2\) covariance matrix of \((RIPD_{R,j}, RIPD_{S,j})\). Under \(H_0\), \(RIPD_{RS,j}\) asymptotically follows a \(\chi^2\) distribution with 2 degrees of freedom. \(RIPD_{RS}\) is the recommended statistic in practice because it is sensitive to both uniform and nonuniform drift and addresses potential inflation of the family-wise Type I error that arises from applying \(RIPD_R\) and \(RIPD_S\) separately to the same item.
Diagnosing the Nature of Drift
The pattern of flagging across the three statistics can help diagnose the type of drift. If an item is flagged by \(RIPD_R\) (and possibly \(RIPD_{RS}\)) but not \(RIPD_S\), uniform drift is indicated (e.g., difficulty shift). If flagged by \(RIPD_S\) (and possibly \(RIPD_{RS}\)) but not \(RIPD_R\), nonuniform drift is suggested (e.g., discrimination change). Items flagged by all statistics or by \(RIPD_{RS}\) alone likely exhibit mixed drift.
CAT-Specific Workflow
The RIPD procedure for CAT consists of three steps (Lim & Han, in press):
Focal group CAT: The current cohort of examinees takes the CAT using the operational (potentially drifted) item pool. Each examinee receives only a subset of items; the resulting response matrix is sparse. The ML ability estimates \(\hat{\theta}\) from this step are retained.
Synthetic reference group construction: The focal group's \(\hat{\theta}\) values are treated as true abilities. Item responses are generated from the original (pre-calibrated, drift-free) item parameters, and an independent CAT is administered. This creates a synthetic reference group that matches the focal group's ability distribution, so that any systematic differences in residuals can be attributed to IPD rather than ability confounds. The reference group size is controlled by a replication factor: e.g., 1F reuses the focal \(\hat{\theta}\) values once (N_ref = N_foc), while kF replicates them k times. Larger reference groups (3F-8F) reduce sampling variability in reference residuals and improve detection power, with marginal gains typically diminishing beyond 5F.
RIPD computation with purification: Residuals are computed for both groups using the original item parameters, and the three RIPD statistics are evaluated item-by-item. Items whose Z-test (for \(RIPD_R\) or \(RIPD_S\)) or chi-square test (for \(RIPD_{RS}\)) exceeds the critical value at level
alphaare flagged as drifting.
Purification Procedure
When purify = TRUE, an iterative purification procedure adapted from
Lim et al. (2022) is applied to mitigate the bias in ability estimates caused
by drifted items–analogous to the contaminating effect of DIF items on
matching variables. At each iteration:
The item with the most statistically significant drift statistic (smallest p-value) among currently unflagged items is identified and flagged as a potential IPD item.
Ability estimates are recomputed excluding all currently flagged items.
RIPD statistics are recalculated using the updated ability estimates for the remaining items.
The process continues until no additional items are flagged (convergence) or
the maximum number of iterations (max.iter) is reached. The statistic
used to drive purification is specified by purify.by;
"ripdrs" (\(RIPD_{RS}\)) is recommended as it is sensitive to both
types of drift.
Key Items and item.skip
In CAT contexts, many items in the pool receive few responses and thus lack
sufficient data for reliable IPD analysis. The item.skip argument
allows users to exclude such items (e.g., low-exposure non-key items) from
the analysis. In practice, key items for RIPD evaluation are typically
identified through a preliminary CAT simulation as those with the highest
average exposure frequencies under the intended operational settings.
Methods (by class)
ripd(default): Default method for computing the three RIPD statistics using a data framexthat contains item metadataripd(est_irt): An object created by the functionest_irt().ripd(est_item): An object created by the functionest_item().
References
Lim, H., & Choe, E. M. (2023). Detecting differential item functioning in CAT using IRT residual DIF approach. Journal of Educational Measurement, 60(4), 626-650. doi:10.1111/jedm.12366 .
Lim, H., Choe, E. M., & Han, K. T. (2022). A residual-based differential item functioning detection framework in item response theory. Journal of Educational Measurement, 59(1), 80-104. doi:10.1111/jedm.12313 .
Lim, H., & Han, K. T. (in press). IRT residual-based approach to detecting item parameter drift in CAT. Journal of Educational and Behavioral Statistics.
Author
Hwanggyu Lim hglim83@gmail.com
Examples
# \donttest{
## --- RIPD Example: Detecting IPD in CAT ---------------------------------
##
## Background (Lim & Han, in press):
## In CAT-based IPD detection using RIPD, the reference group is
## "synthetic" -- created by re-administering a CAT to examinees whose
## true abilities are set equal to the focal group's ML theta estimates,
## using the ORIGINAL (pre-drift) item parameters. This eliminates the
## need for recalibration and makes RIPD directly applicable to
## operational CAT settings.
##
## The simIPD dataset contains:
## - foc_resp / foc_score : focal group CAT responses + ML theta estimates
## (IPD items: a and b each drifted by -0.5)
## - ref_resp / ref_score : synthetic reference group CAT responses + ML
## theta estimates (original parameters, 1F size)
## - item_par : original (non-drifted) 360-item pool in irtQ format
## - key_item : indices of 90 key items (highly exposed in CAT)
## - item.skip : indices of 270 non-key items (excluded from RIPD)
## - ipd_item : indices of 18 truly drifted items (ground truth)
## -------------------------------------------------------------------------
data(simIPD)
## Step 1. Combine focal and synthetic reference group data
## (reference group first, then focal group -- as in the paper)
data <- rbind(simIPD$ref_resp, simIPD$foc_resp)
score <- c(simIPD$ref_score, simIPD$foc_score)
group <- c(rep(0, nrow(simIPD$ref_resp)), # 0 = reference
rep(1, nrow(simIPD$foc_resp))) # 1 = focal
## Step 2. Run RIPD with purification (recommended statistic: RIPD_RS)
## item.skip excludes the 270 non-key items from analysis
ripd_result <- ripd(
x = simIPD$item_par,
data = data,
score = score,
group = group,
focal.name = 1, # focal group is coded as 1
item.skip = simIPD$item.skip,
D = 1.7,
alpha = 0.05,
purify = TRUE,
purify.by = "ripdrs", # purify using RIPD_RS (combined statistic)
max.iter = 30,
method = "ML",
range = c(-5, 5)
)
#> Purification started...
#>
Iteration: 1
Iteration: 2
Iteration: 3
Iteration: 4
Iteration: 5
Iteration: 6
Iteration: 7
Iteration: 8
Iteration: 9
Iteration: 10
Iteration: 11
Iteration: 12
Iteration: 13
Iteration: 14
Iteration: 15
Iteration: 16
Iteration: 17
Iteration: 18
Iteration: 19
Iteration: 20
#> Purification is finished.
## Step 3. Review RIPD_RS results (with purification)
print(ripd_result, what = "with_purify")
#> $no_purify
#> $no_purify$ipd_stat
#> id ripdr z.ripdr ripds z.ripds ripdrs p.ripdr p.ripds p.ripdrs n.ref
#> 1 I1 NA NA NA NA NA NA NA NA 2
#> 2 I2 0.0173 0.5402 -0.0141 -1.2624 1.8579 0.5891 0.2068 0.3950 429
#> 3 I3 0.0318 1.3576 -0.0074 -0.9337 2.2584 0.1746 0.3504 0.3233 698
#> 4 I4 NA NA NA NA NA NA NA NA 221
#> 5 I5 NA NA NA NA NA NA NA NA 85
#> 6 I6 NA NA NA NA NA NA NA NA 61
#> 7 I7 NA NA NA NA NA NA NA NA 104
#> 8 I8 NA NA NA NA NA NA NA NA 179
#> 9 I9 NA NA NA NA NA NA NA NA 19
#> 10 I10 -0.0278 -0.9569 0.0134 1.6889 2.9107 0.3386 0.0912 0.2333 510
#> 11 I11 NA NA NA NA NA NA NA NA 176
#> 12 I12 NA NA NA NA NA NA NA NA 0
#> 13 I13 0.0279 1.1219 0.0043 0.2301 3.7262 0.2619 0.8180 0.1552 596
#> 14 I14 -0.0259 -0.8345 0.0033 0.0311 2.1789 0.4040 0.9752 0.3364 442
#> 15 I15 -0.0300 -0.9889 0.0028 0.0746 1.9921 0.3227 0.9405 0.3693 472
#> 16 I16 NA NA NA NA NA NA NA NA 21
#> 17 I17 NA NA NA NA NA NA NA NA 0
#> 18 I18 0.0203 0.8273 0.0049 0.3589 1.1542 0.4080 0.7197 0.5615 664
#> 19 I19 NA NA NA NA NA NA NA NA 0
#> 20 I20 -0.0515 -1.9953 0.0251 1.9921 4.8577 0.0460 0.0464 0.0881 520
#> 21 I21 NA NA NA NA NA NA NA NA 114
#> 22 I22 NA NA NA NA NA NA NA NA 0
#> 23 I23 -0.0248 -1.0644 0.0160 1.1964 1.8893 0.2871 0.2315 0.3888 583
#> 24 I24 NA NA NA NA NA NA NA NA 0
#> 25 I25 0.0310 1.0641 -0.0015 -0.3075 1.1650 0.2873 0.7585 0.5585 506
#> 26 I26 0.0971 3.5756 -0.0343 -3.2040 13.0698 0.0003 0.0014 0.0015 515
#> 27 I27 NA NA NA NA NA NA NA NA 0
#> 28 I28 NA NA NA NA NA NA NA NA 83
#> 29 I29 NA NA NA NA NA NA NA NA 27
#> 30 I30 NA NA NA NA NA NA NA NA 0
#> 31 I31 -0.0200 -0.8243 -0.0005 -0.4137 1.5087 0.4098 0.6791 0.4703 672
#> 32 I32 NA NA NA NA NA NA NA NA 0
#> 33 I33 NA NA NA NA NA NA NA NA 351
#> 34 I34 NA NA NA NA NA NA NA NA 0
#> 35 I35 0.0098 0.3954 -0.0207 -1.9332 3.8555 0.6925 0.0532 0.1455 656
#> 36 I36 NA NA NA NA NA NA NA NA 67
#> 37 I37 NA NA NA NA NA NA NA NA 69
#> 38 I38 NA NA NA NA NA NA NA NA 136
#> 39 I39 NA NA NA NA NA NA NA NA 145
#> 40 I40 NA NA NA NA NA NA NA NA 107
#> 41 I41 NA NA NA NA NA NA NA NA 69
#> 42 I42 0.0721 2.3928 -0.0115 -1.5931 5.7734 0.0167 0.1111 0.0558 474
#> 43 I43 -0.0169 -0.6013 0.0058 0.5140 0.3780 0.5477 0.6073 0.8278 508
#> 44 I44 NA NA NA NA NA NA NA NA 0
#> 45 I45 NA NA NA NA NA NA NA NA 63
#> 46 I46 NA NA NA NA NA NA NA NA 186
#> 47 I47 NA NA NA NA NA NA NA NA 0
#> 48 I48 NA NA NA NA NA NA NA NA 382
#> 49 I49 NA NA NA NA NA NA NA NA 219
#> 50 I50 NA NA NA NA NA NA NA NA 0
#> 51 I51 NA NA NA NA NA NA NA NA 321
#> 52 I52 NA NA NA NA NA NA NA NA 324
#> 53 I53 NA NA NA NA NA NA NA NA 295
#> 54 I54 NA NA NA NA NA NA NA NA 0
#> 55 I55 0.1179 4.2887 -0.0158 -1.8164 21.2750 0.0000 0.0693 0.0000 505
#> 56 I56 NA NA NA NA NA NA NA NA 0
#> 57 I57 NA NA NA NA NA NA NA NA 24
#> 58 I58 0.1145 5.2697 -0.0065 0.0173 34.1081 0.0000 0.9862 0.0000 669
#> 59 I59 NA NA NA NA NA NA NA NA 144
#> 60 I60 NA NA NA NA NA NA NA NA 131
#> 61 I61 -0.0085 -0.3111 0.0128 1.3598 2.1587 0.7557 0.1739 0.3398 554
#> 62 I62 -0.0056 -0.1740 -0.0045 -0.0297 0.0487 0.8619 0.9763 0.9760 439
#> 63 I63 NA NA NA NA NA NA NA NA 139
#> 64 I64 0.0207 0.8605 0.0007 -0.5985 0.7438 0.3895 0.5495 0.6894 634
#> 65 I65 NA NA NA NA NA NA NA NA 0
#> 66 I66 NA NA NA NA NA NA NA NA 403
#> 67 I67 NA NA NA NA NA NA NA NA 152
#> 68 I68 -0.0159 -0.5147 -0.0013 -0.1165 0.6972 0.6067 0.9073 0.7057 457
#> 69 I69 -0.0589 -1.7884 0.0002 0.3448 4.7189 0.0737 0.7303 0.0945 406
#> 70 I70 NA NA NA NA NA NA NA NA 295
#> 71 I71 NA NA NA NA NA NA NA NA 2
#> 72 I72 NA NA NA NA NA NA NA NA 328
#> 73 I73 NA NA NA NA NA NA NA NA 0
#> 74 I74 -0.0109 -0.4284 -0.0019 0.0756 0.2151 0.6684 0.9397 0.8980 619
#> 75 I75 -0.0516 -1.8258 0.0027 0.2684 5.7464 0.0679 0.7884 0.0565 528
#> 76 I76 NA NA NA NA NA NA NA NA 1
#> 77 I77 NA NA NA NA NA NA NA NA 0
#> 78 I78 NA NA NA NA NA NA NA NA 313
#> 79 I79 NA NA NA NA NA NA NA NA 271
#> 80 I80 NA NA NA NA NA NA NA NA 395
#> 81 I81 NA NA NA NA NA NA NA NA 389
#> 82 I82 NA NA NA NA NA NA NA NA 0
#> 83 I83 NA NA NA NA NA NA NA NA 317
#> 84 I84 -0.0185 -0.5784 -0.0084 -0.7806 2.6149 0.5630 0.4350 0.2705 443
#> 85 I85 NA NA NA NA NA NA NA NA 390
#> 86 I86 NA NA NA NA NA NA NA NA 0
#> 87 I87 NA NA NA NA NA NA NA NA 60
#> 88 I88 NA NA NA NA NA NA NA NA 265
#> 89 I89 NA NA NA NA NA NA NA NA 324
#> 90 I90 NA NA NA NA NA NA NA NA 374
#> 91 I91 NA NA NA NA NA NA NA NA 11
#> 92 I92 NA NA NA NA NA NA NA NA 57
#> 93 I93 NA NA NA NA NA NA NA NA 0
#> 94 I94 NA NA NA NA NA NA NA NA 1
#> 95 I95 NA NA NA NA NA NA NA NA 323
#> 96 I96 NA NA NA NA NA NA NA NA 90
#> 97 I97 0.0839 2.9348 -0.0117 -1.1723 9.5752 0.0033 0.2411 0.0083 520
#> 98 I98 NA NA NA NA NA NA NA NA 165
#> 99 I99 NA NA NA NA NA NA NA NA 250
#> 100 I100 NA NA NA NA NA NA NA NA 30
#> 101 I101 NA NA NA NA NA NA NA NA 28
#> 102 I102 NA NA NA NA NA NA NA NA 0
#> 103 I103 NA NA NA NA NA NA NA NA 265
#> 104 I104 NA NA NA NA NA NA NA NA 1
#> 105 I105 NA NA NA NA NA NA NA NA 0
#> 106 I106 NA NA NA NA NA NA NA NA 345
#> 107 I107 NA NA NA NA NA NA NA NA 169
#> 108 I108 NA NA NA NA NA NA NA NA 0
#> 109 I109 NA NA NA NA NA NA NA NA 344
#> 110 I110 NA NA NA NA NA NA NA NA 406
#> 111 I111 NA NA NA NA NA NA NA NA 0
#> 112 I112 NA NA NA NA NA NA NA NA 0
#> 113 I113 NA NA NA NA NA NA NA NA 1
#> 114 I114 NA NA NA NA NA NA NA NA 348
#> 115 I115 NA NA NA NA NA NA NA NA 349
#> 116 I116 NA NA NA NA NA NA NA NA 328
#> 117 I117 NA NA NA NA NA NA NA NA 139
#> 118 I118 NA NA NA NA NA NA NA NA 288
#> 119 I119 -0.0268 -0.9116 0.0053 0.8507 0.9770 0.3620 0.3949 0.6135 486
#> 120 I120 NA NA NA NA NA NA NA NA 0
#> 121 I121 NA NA NA NA NA NA NA NA 347
#> 122 I122 NA NA NA NA NA NA NA NA 0
#> 123 I123 NA NA NA NA NA NA NA NA 218
#> 124 I124 NA NA NA NA NA NA NA NA 7
#> 125 I125 NA NA NA NA NA NA NA NA 299
#> 126 I126 -0.0299 -1.0021 0.0071 0.7132 1.0042 0.3163 0.4757 0.6052 480
#> 127 I127 NA NA NA NA NA NA NA NA 2
#> 128 I128 NA NA NA NA NA NA NA NA 362
#> 129 I129 0.1228 4.8055 0.0054 0.6920 32.1091 0.0000 0.4889 0.0000 583
#> 130 I130 -0.0704 -2.2963 0.0346 2.5760 8.5053 0.0217 0.0100 0.0142 432
#> 131 I131 NA NA NA NA NA NA NA NA 0
#> 132 I132 NA NA NA NA NA NA NA NA 53
#> 133 I133 -0.0192 -0.7345 0.0009 -0.0101 0.9787 0.4627 0.9920 0.6130 602
#> 134 I134 NA NA NA NA NA NA NA NA 168
#> 135 I135 NA NA NA NA NA NA NA NA 193
#> 136 I136 NA NA NA NA NA NA NA NA 21
#> 137 I137 NA NA NA NA NA NA NA NA 0
#> 138 I138 0.1379 5.4350 0.0146 1.6850 40.5860 0.0000 0.0920 0.0000 621
#> 139 I139 NA NA NA NA NA NA NA NA 302
#> 140 I140 NA NA NA NA NA NA NA NA 0
#> 141 I141 NA NA NA NA NA NA NA NA 139
#> 142 I142 NA NA NA NA NA NA NA NA 192
#> 143 I143 0.0399 1.3088 -0.0188 -1.4780 2.3948 0.1906 0.1394 0.3020 457
#> 144 I144 NA NA NA NA NA NA NA NA 0
#> 145 I145 0.1743 6.8927 -0.0153 -1.9528 58.8563 0.0000 0.0508 0.0000 615
#> 146 I146 -0.0186 -0.7186 0.0045 -0.1452 1.0728 0.4724 0.8846 0.5848 600
#> 147 I147 0.0032 0.1012 0.0009 0.3014 0.2756 0.9194 0.7631 0.8713 437
#> 148 I148 NA NA NA NA NA NA NA NA 274
#> 149 I149 0.0994 3.3384 -0.0135 -1.4647 11.6110 0.0008 0.1430 0.0030 496
#> 150 I150 NA NA NA NA NA NA NA NA 369
#> 151 I151 NA NA NA NA NA NA NA NA 214
#> 152 I152 -0.0393 -1.4856 0.0209 1.9569 5.1356 0.1374 0.0504 0.0767 583
#> 153 I153 0.0137 0.6014 -0.0035 -0.1178 0.3618 0.5476 0.9062 0.8345 713
#> 154 I154 NA NA NA NA NA NA NA NA 274
#> 155 I155 NA NA NA NA NA NA NA NA 0
#> 156 I156 NA NA NA NA NA NA NA NA 0
#> 157 I157 NA NA NA NA NA NA NA NA 98
#> 158 I158 NA NA NA NA NA NA NA NA 374
#> 159 I159 NA NA NA NA NA NA NA NA 108
#> 160 I160 NA NA NA NA NA NA NA NA 227
#> 161 I161 NA NA NA NA NA NA NA NA 431
#> 162 I162 -0.0188 -0.7486 0.0105 0.1881 0.8367 0.4541 0.8508 0.6581 576
#> 163 I163 -0.0497 -1.8972 0.0025 0.2901 3.7005 0.0578 0.7717 0.1572 621
#> 164 I164 NA NA NA NA NA NA NA NA 0
#> 165 I165 NA NA NA NA NA NA NA NA 0
#> 166 I166 NA NA NA NA NA NA NA NA 127
#> 167 I167 -0.0011 -0.0422 -0.0047 0.0904 0.0083 0.9664 0.9279 0.9959 564
#> 168 I168 0.0291 0.9827 -0.0066 -0.7129 1.0229 0.3257 0.4759 0.5996 467
#> 169 I169 NA NA NA NA NA NA NA NA 415
#> 170 I170 NA NA NA NA NA NA NA NA 425
#> 171 I171 NA NA NA NA NA NA NA NA 299
#> 172 I172 NA NA NA NA NA NA NA NA 110
#> 173 I173 NA NA NA NA NA NA NA NA 439
#> 174 I174 NA NA NA NA NA NA NA NA 0
#> 175 I175 NA NA NA NA NA NA NA NA 434
#> 176 I176 NA NA NA NA NA NA NA NA 1
#> 177 I177 NA NA NA NA NA NA NA NA 373
#> 178 I178 NA NA NA NA NA NA NA NA 160
#> 179 I179 NA NA NA NA NA NA NA NA 414
#> 180 I180 NA NA NA NA NA NA NA NA 223
#> 181 I181 0.0924 4.0612 -0.0047 -1.0485 18.3583 0.0000 0.2944 0.0001 666
#> 182 I182 NA NA NA NA NA NA NA NA 0
#> 183 I183 NA NA NA NA NA NA NA NA 375
#> 184 I184 0.0904 3.2589 -0.0198 -2.2674 10.6479 0.0011 0.0234 0.0049 546
#> 185 I185 NA NA NA NA NA NA NA NA 172
#> 186 I186 NA NA NA NA NA NA NA NA 383
#> 187 I187 0.0132 0.4007 -0.0078 -0.4528 0.2190 0.6887 0.6507 0.8963 414
#> 188 I188 -0.0232 -0.9745 0.0175 1.8231 3.3413 0.3298 0.0683 0.1881 692
#> 189 I189 NA NA NA NA NA NA NA NA 154
#> 190 I190 NA NA NA NA NA NA NA NA 121
#> 191 I191 NA NA NA NA NA NA NA NA 314
#> 192 I192 NA NA NA NA NA NA NA NA 23
#> 193 I193 NA NA NA NA NA NA NA NA 0
#> 194 I194 NA NA NA NA NA NA NA NA 184
#> 195 I195 NA NA NA NA NA NA NA NA 210
#> 196 I196 NA NA NA NA NA NA NA NA 0
#> 197 I197 NA NA NA NA NA NA NA NA 57
#> 198 I198 NA NA NA NA NA NA NA NA 19
#> 199 I199 -0.0250 -1.0192 0.0033 0.2906 1.0484 0.3081 0.7714 0.5920 634
#> 200 I200 NA NA NA NA NA NA NA NA 327
#> 201 I201 NA NA NA NA NA NA NA NA 0
#> 202 I202 -0.0544 -1.8924 0.0019 0.1842 4.3527 0.0584 0.8539 0.1135 529
#> 203 I203 0.0886 3.3745 -0.0117 -1.0398 22.1712 0.0007 0.2984 0.0000 549
#> 204 I204 NA NA NA NA NA NA NA NA 4
#> 205 I205 NA NA NA NA NA NA NA NA 3
#> 206 I206 NA NA NA NA NA NA NA NA 0
#> 207 I207 NA NA NA NA NA NA NA NA 3
#> 208 I208 NA NA NA NA NA NA NA NA 212
#> 209 I209 NA NA NA NA NA NA NA NA 288
#> 210 I210 -0.0012 -0.0552 0.0103 1.0092 1.0409 0.9560 0.3129 0.5942 711
#> 211 I211 NA NA NA NA NA NA NA NA 180
#> 212 I212 NA NA NA NA NA NA NA NA 1
#> 213 I213 NA NA NA NA NA NA NA NA 36
#> 214 I214 NA NA NA NA NA NA NA NA 3
#> 215 I215 -0.0805 -2.6342 0.0196 2.0276 7.3650 0.0084 0.0426 0.0252 474
#> 216 I216 NA NA NA NA NA NA NA NA 76
#> 217 I217 NA NA NA NA NA NA NA NA 274
#> 218 I218 -0.0273 -0.8513 -0.0033 0.3311 0.9688 0.3946 0.7406 0.6161 424
#> 219 I219 NA NA NA NA NA NA NA NA 0
#> 220 I220 NA NA NA NA NA NA NA NA 12
#> 221 I221 NA NA NA NA NA NA NA NA 400
#> 222 I222 NA NA NA NA NA NA NA NA 0
#> 223 I223 NA NA NA NA NA NA NA NA 0
#> 224 I224 NA NA NA NA NA NA NA NA 157
#> 225 I225 NA NA NA NA NA NA NA NA 0
#> 226 I226 NA NA NA NA NA NA NA NA 161
#> 227 I227 -0.0308 -1.2279 0.0094 0.4349 1.5865 0.2195 0.6636 0.4524 613
#> 228 I228 NA NA NA NA NA NA NA NA 334
#> 229 I229 -0.0380 -1.1757 0.0063 0.6852 1.4027 0.2397 0.4932 0.4959 440
#> 230 I230 NA NA NA NA NA NA NA NA 123
#> 231 I231 -0.0729 -2.8009 0.0220 1.8729 7.9172 0.0051 0.0611 0.0191 575
#> 232 I232 NA NA NA NA NA NA NA NA 0
#> 233 I233 NA NA NA NA NA NA NA NA 49
#> 234 I234 NA NA NA NA NA NA NA NA 106
#> 235 I235 -0.0425 -1.4764 0.0044 0.5895 2.4439 0.1398 0.5556 0.2946 509
#> 236 I236 0.0114 0.4563 0.0204 2.0225 9.9184 0.6482 0.0431 0.0070 638
#> 237 I237 -0.0149 -0.5266 -0.0042 -0.7598 1.5801 0.5984 0.4473 0.4538 550
#> 238 I238 NA NA NA NA NA NA NA NA 360
#> 239 I239 NA NA NA NA NA NA NA NA 357
#> 240 I240 NA NA NA NA NA NA NA NA 326
#> 241 I241 NA NA NA NA NA NA NA NA 0
#> 242 I242 0.1177 3.8101 -0.0070 -1.2979 16.3370 0.0001 0.1943 0.0003 477
#> 243 I243 NA NA NA NA NA NA NA NA 221
#> 244 I244 -0.0489 -1.8529 0.0187 1.8617 4.0210 0.0639 0.0626 0.1339 562
#> 245 I245 NA NA NA NA NA NA NA NA 244
#> 246 I246 0.1313 5.7388 -0.0001 0.2751 44.3993 0.0000 0.7832 0.0000 692
#> 247 I247 NA NA NA NA NA NA NA NA 70
#> 248 I248 -0.0114 -0.3972 0.0055 0.2600 0.1773 0.6912 0.7949 0.9152 457
#> 249 I249 0.0156 0.5415 0.0022 -0.0473 0.3072 0.5882 0.9623 0.8576 486
#> 250 I250 -0.0170 -0.6496 -0.0003 -0.0252 0.7054 0.5159 0.9799 0.7028 555
#> 251 I251 NA NA NA NA NA NA NA NA 362
#> 252 I252 0.0915 3.9694 -0.0079 -0.6548 18.7998 0.0001 0.5126 0.0001 644
#> 253 I253 -0.0024 -0.0776 -0.0068 -0.5146 0.3591 0.9381 0.6068 0.8356 480
#> 254 I254 NA NA NA NA NA NA NA NA 363
#> 255 I255 NA NA NA NA NA NA NA NA 0
#> 256 I256 NA NA NA NA NA NA NA NA 377
#> 257 I257 NA NA NA NA NA NA NA NA 187
#> 258 I258 NA NA NA NA NA NA NA NA 442
#> 259 I259 NA NA NA NA NA NA NA NA 242
#> 260 I260 NA NA NA NA NA NA NA NA 71
#> 261 I261 0.0301 1.0613 -0.0083 -1.1357 1.3132 0.2885 0.2561 0.5186 493
#> 262 I262 NA NA NA NA NA NA NA NA 96
#> 263 I263 NA NA NA NA NA NA NA NA 168
#> 264 I264 NA NA NA NA NA NA NA NA 175
#> 265 I265 NA NA NA NA NA NA NA NA 0
#> 266 I266 NA NA NA NA NA NA NA NA 226
#> 267 I267 NA NA NA NA NA NA NA NA 128
#> 268 I268 NA NA NA NA NA NA NA NA 376
#> 269 I269 NA NA NA NA NA NA NA NA 0
#> 270 I270 0.0355 1.1734 -0.0035 -0.2582 2.6968 0.2407 0.7963 0.2597 434
#> 271 I271 NA NA NA NA NA NA NA NA 0
#> 272 I272 0.0019 0.0689 -0.0040 -0.3774 0.2073 0.9451 0.7059 0.9015 565
#> 273 I273 NA NA NA NA NA NA NA NA 362
#> 274 I274 NA NA NA NA NA NA NA NA 14
#> 275 I275 NA NA NA NA NA NA NA NA 21
#> 276 I276 -0.0106 -0.3810 -0.0057 -0.9903 3.0746 0.7032 0.3220 0.2150 548
#> 277 I277 -0.0903 -2.8898 0.0251 2.2772 8.3510 0.0039 0.0228 0.0154 442
#> 278 I278 NA NA NA NA NA NA NA NA 0
#> 279 I279 NA NA NA NA NA NA NA NA 0
#> 280 I280 NA NA NA NA NA NA NA NA 296
#> 281 I281 NA NA NA NA NA NA NA NA 211
#> 282 I282 NA NA NA NA NA NA NA NA 373
#> 283 I283 NA NA NA NA NA NA NA NA 252
#> 284 I284 NA NA NA NA NA NA NA NA 0
#> 285 I285 NA NA NA NA NA NA NA NA 187
#> 286 I286 NA NA NA NA NA NA NA NA 0
#> 287 I287 NA NA NA NA NA NA NA NA 6
#> 288 I288 NA NA NA NA NA NA NA NA 337
#> 289 I289 NA NA NA NA NA NA NA NA 0
#> 290 I290 NA NA NA NA NA NA NA NA 260
#> 291 I291 NA NA NA NA NA NA NA NA 0
#> 292 I292 NA NA NA NA NA NA NA NA 0
#> 293 I293 NA NA NA NA NA NA NA NA 0
#> 294 I294 NA NA NA NA NA NA NA NA 339
#> 295 I295 NA NA NA NA NA NA NA NA 0
#> 296 I296 -0.0334 -1.3662 0.0067 -0.1125 2.0527 0.1719 0.9104 0.3583 636
#> 297 I297 NA NA NA NA NA NA NA NA 121
#> 298 I298 -0.0341 -1.4716 0.0084 0.6119 2.2112 0.1411 0.5406 0.3310 713
#> 299 I299 NA NA NA NA NA NA NA NA 188
#> 300 I300 -0.0199 -0.7492 0.0025 -0.0173 0.6740 0.4538 0.9862 0.7139 586
#> 301 I301 NA NA NA NA NA NA NA NA 327
#> 302 I302 NA NA NA NA NA NA NA NA 395
#> 303 I303 NA NA NA NA NA NA NA NA 188
#> 304 I304 NA NA NA NA NA NA NA NA 311
#> 305 I305 NA NA NA NA NA NA NA NA 0
#> 306 I306 -0.0526 -1.8044 0.0042 -0.1251 4.0561 0.0712 0.9004 0.1316 439
#> 307 I307 NA NA NA NA NA NA NA NA 1
#> 308 I308 NA NA NA NA NA NA NA NA 110
#> 309 I309 NA NA NA NA NA NA NA NA 140
#> 310 I310 0.1095 3.9630 -0.0164 -1.6322 17.4346 0.0001 0.1026 0.0002 523
#> 311 I311 -0.0548 -1.7373 0.0027 0.3852 4.4743 0.0823 0.7001 0.1068 432
#> 312 I312 -0.0717 -2.6338 0.0124 0.8650 7.0911 0.0084 0.3870 0.0289 506
#> 313 I313 NA NA NA NA NA NA NA NA 0
#> 314 I314 NA NA NA NA NA NA NA NA 301
#> 315 I315 NA NA NA NA NA NA NA NA 0
#> 316 I316 NA NA NA NA NA NA NA NA 0
#> 317 I317 NA NA NA NA NA NA NA NA 63
#> 318 I318 NA NA NA NA NA NA NA NA 340
#> 319 I319 NA NA NA NA NA NA NA NA 369
#> 320 I320 NA NA NA NA NA NA NA NA 349
#> 321 I321 NA NA NA NA NA NA NA NA 38
#> 322 I322 -0.0326 -1.3222 0.0101 1.1491 1.9405 0.1861 0.2505 0.3790 626
#> 323 I323 NA NA NA NA NA NA NA NA 218
#> 324 I324 NA NA NA NA NA NA NA NA 418
#> 325 I325 -0.0085 -0.3392 0.0009 -0.3046 0.5289 0.7345 0.7607 0.7676 627
#> 326 I326 NA NA NA NA NA NA NA NA 252
#> 327 I327 -0.0526 -1.8413 0.0125 1.1084 3.6897 0.0656 0.2677 0.1581 506
#> 328 I328 NA NA NA NA NA NA NA NA 374
#> 329 I329 NA NA NA NA NA NA NA NA 124
#> 330 I330 NA NA NA NA NA NA NA NA 177
#> 331 I331 -0.0099 -0.3368 -0.0022 -0.5987 0.8542 0.7362 0.5493 0.6524 504
#> 332 I332 NA NA NA NA NA NA NA NA 326
#> 333 I333 NA NA NA NA NA NA NA NA 127
#> 334 I334 0.1759 7.1779 -0.0083 -0.9826 59.8699 0.0000 0.3258 0.0000 659
#> 335 I335 NA NA NA NA NA NA NA NA 89
#> 336 I336 0.1108 3.7849 -0.0009 -0.3138 15.9985 0.0002 0.7537 0.0003 520
#> 337 I337 -0.0423 -1.6608 0.0030 0.2507 3.7244 0.0968 0.8021 0.1553 596
#> 338 I338 NA NA NA NA NA NA NA NA 350
#> 339 I339 NA NA NA NA NA NA NA NA 0
#> 340 I340 NA NA NA NA NA NA NA NA 239
#> 341 I341 NA NA NA NA NA NA NA NA 316
#> 342 I342 NA NA NA NA NA NA NA NA 0
#> 343 I343 NA NA NA NA NA NA NA NA 0
#> 344 I344 NA NA NA NA NA NA NA NA 0
#> 345 I345 NA NA NA NA NA NA NA NA 0
#> 346 I346 NA NA NA NA NA NA NA NA 167
#> 347 I347 -0.0060 -0.2348 -0.0061 -0.7443 1.4252 0.8144 0.4567 0.4904 610
#> 348 I348 NA NA NA NA NA NA NA NA 429
#> 349 I349 NA NA NA NA NA NA NA NA 67
#> 350 I350 NA NA NA NA NA NA NA NA 151
#> 351 I351 -0.0651 -2.4330 0.0083 1.0562 6.0896 0.0150 0.2909 0.0476 549
#> 352 I352 NA NA NA NA NA NA NA NA 0
#> 353 I353 NA NA NA NA NA NA NA NA 0
#> 354 I354 -0.0308 -1.0418 -0.0124 -0.9452 6.1044 0.2975 0.3446 0.0473 474
#> 355 I355 NA NA NA NA NA NA NA NA 298
#> 356 I356 NA NA NA NA NA NA NA NA 273
#> 357 I357 NA NA NA NA NA NA NA NA 77
#> 358 I358 -0.0230 -0.9031 0.0151 2.1250 5.1635 0.3665 0.0336 0.0756 634
#> 359 I359 NA NA NA NA NA NA NA NA 0
#> 360 I360 NA NA NA NA NA NA NA NA 213
#> n.foc n.total
#> 1 4 6
#> 2 433 862
#> 3 700 1398
#> 4 235 456
#> 5 73 158
#> 6 56 117
#> 7 108 212
#> 8 184 363
#> 9 14 33
#> 10 516 1026
#> 11 158 334
#> 12 1 1
#> 13 598 1194
#> 14 453 895
#> 15 482 954
#> 16 17 38
#> 17 0 0
#> 18 665 1329
#> 19 0 0
#> 20 492 1012
#> 21 127 241
#> 22 0 0
#> 23 552 1135
#> 24 0 0
#> 25 506 1012
#> 26 521 1036
#> 27 0 0
#> 28 87 170
#> 29 19 46
#> 30 0 0
#> 31 678 1350
#> 32 0 0
#> 33 356 707
#> 34 0 0
#> 35 657 1313
#> 36 65 132
#> 37 69 138
#> 38 129 265
#> 39 136 281
#> 40 99 206
#> 41 61 130
#> 42 479 953
#> 43 510 1018
#> 44 0 0
#> 45 74 137
#> 46 172 358
#> 47 0 0
#> 48 386 768
#> 49 208 427
#> 50 0 0
#> 51 318 639
#> 52 327 651
#> 53 296 591
#> 54 0 0
#> 55 512 1017
#> 56 0 0
#> 57 21 45
#> 58 665 1334
#> 59 137 281
#> 60 121 252
#> 61 557 1111
#> 62 441 880
#> 63 123 262
#> 64 640 1274
#> 65 0 0
#> 66 404 807
#> 67 156 308
#> 68 460 917
#> 69 398 804
#> 70 276 571
#> 71 1 3
#> 72 329 657
#> 73 0 0
#> 74 621 1240
#> 75 536 1064
#> 76 0 1
#> 77 0 0
#> 78 311 624
#> 79 278 549
#> 80 407 802
#> 81 392 781
#> 82 0 0
#> 83 300 617
#> 84 443 886
#> 85 394 784
#> 86 0 0
#> 87 52 112
#> 88 271 536
#> 89 307 631
#> 90 384 758
#> 91 7 18
#> 92 56 113
#> 93 0 0
#> 94 3 4
#> 95 329 652
#> 96 93 183
#> 97 529 1049
#> 98 138 303
#> 99 250 500
#> 100 35 65
#> 101 23 51
#> 102 0 0
#> 103 252 517
#> 104 1 2
#> 105 0 0
#> 106 350 695
#> 107 182 351
#> 108 0 0
#> 109 354 698
#> 110 406 812
#> 111 0 0
#> 112 0 0
#> 113 1 2
#> 114 354 702
#> 115 338 687
#> 116 313 641
#> 117 142 281
#> 118 288 576
#> 119 491 977
#> 120 0 0
#> 121 352 699
#> 122 0 0
#> 123 207 425
#> 124 13 20
#> 125 302 601
#> 126 483 963
#> 127 2 4
#> 128 369 731
#> 129 577 1160
#> 130 410 842
#> 131 0 0
#> 132 42 95
#> 133 603 1205
#> 134 174 342
#> 135 184 377
#> 136 14 35
#> 137 0 0
#> 138 624 1245
#> 139 289 591
#> 140 0 0
#> 141 148 287
#> 142 201 393
#> 143 464 921
#> 144 0 0
#> 145 622 1237
#> 146 598 1198
#> 147 447 884
#> 148 268 542
#> 149 503 999
#> 150 367 736
#> 151 221 435
#> 152 588 1171
#> 153 716 1429
#> 154 281 555
#> 155 0 0
#> 156 0 0
#> 157 88 186
#> 158 379 753
#> 159 111 219
#> 160 234 461
#> 161 442 873
#> 162 582 1158
#> 163 622 1243
#> 164 0 0
#> 165 0 0
#> 166 136 263
#> 167 568 1132
#> 168 478 945
#> 169 413 828
#> 170 429 854
#> 171 278 577
#> 172 118 228
#> 173 445 884
#> 174 0 0
#> 175 435 869
#> 176 0 1
#> 177 348 721
#> 178 173 333
#> 179 421 835
#> 180 212 435
#> 181 670 1336
#> 182 0 0
#> 183 356 731
#> 184 554 1100
#> 185 172 344
#> 186 385 768
#> 187 420 834
#> 188 695 1387
#> 189 168 322
#> 190 119 240
#> 191 313 627
#> 192 30 53
#> 193 0 0
#> 194 199 383
#> 195 211 421
#> 196 0 0
#> 197 54 111
#> 198 25 44
#> 199 637 1271
#> 200 322 649
#> 201 0 0
#> 202 533 1062
#> 203 558 1107
#> 204 2 6
#> 205 2 5
#> 206 0 0
#> 207 1 4
#> 208 216 428
#> 209 263 551
#> 210 713 1424
#> 211 188 368
#> 212 1 2
#> 213 41 77
#> 214 3 6
#> 215 477 951
#> 216 69 145
#> 217 258 532
#> 218 427 851
#> 219 0 0
#> 220 8 20
#> 221 397 797
#> 222 0 0
#> 223 0 0
#> 224 173 330
#> 225 0 0
#> 226 151 312
#> 227 618 1231
#> 228 347 681
#> 229 445 885
#> 230 128 251
#> 231 583 1158
#> 232 0 0
#> 233 40 89
#> 234 96 202
#> 235 511 1020
#> 236 639 1277
#> 237 556 1106
#> 238 366 726
#> 239 356 713
#> 240 315 641
#> 241 0 0
#> 242 487 964
#> 243 204 425
#> 244 564 1126
#> 245 245 489
#> 246 693 1385
#> 247 63 133
#> 248 459 916
#> 249 492 978
#> 250 560 1115
#> 251 368 730
#> 252 645 1289
#> 253 486 966
#> 254 369 732
#> 255 0 0
#> 256 385 762
#> 257 176 363
#> 258 449 891
#> 259 235 477
#> 260 61 132
#> 261 498 991
#> 262 88 184
#> 263 168 336
#> 264 179 354
#> 265 0 0
#> 266 221 447
#> 267 135 263
#> 268 389 765
#> 269 0 0
#> 270 439 873
#> 271 0 0
#> 272 567 1132
#> 273 368 730
#> 274 21 35
#> 275 16 37
#> 276 549 1097
#> 277 451 893
#> 278 0 0
#> 279 0 0
#> 280 282 578
#> 281 197 408
#> 282 376 749
#> 283 256 508
#> 284 0 0
#> 285 199 386
#> 286 0 0
#> 287 5 11
#> 288 342 679
#> 289 0 0
#> 290 263 523
#> 291 0 0
#> 292 0 0
#> 293 0 0
#> 294 344 683
#> 295 0 0
#> 296 640 1276
#> 297 135 256
#> 298 715 1428
#> 299 189 377
#> 300 589 1175
#> 301 334 661
#> 302 406 801
#> 303 188 376
#> 304 324 635
#> 305 0 0
#> 306 408 847
#> 307 2 3
#> 308 106 216
#> 309 134 274
#> 310 526 1049
#> 311 426 858
#> 312 476 982
#> 313 0 0
#> 314 302 603
#> 315 0 0
#> 316 0 0
#> 317 52 115
#> 318 320 660
#> 319 371 740
#> 320 336 685
#> 321 30 68
#> 322 630 1256
#> 323 206 424
#> 324 430 848
#> 325 626 1253
#> 326 252 504
#> 327 516 1022
#> 328 378 752
#> 329 117 241
#> 330 166 343
#> 331 507 1011
#> 332 332 658
#> 333 110 237
#> 334 658 1317
#> 335 96 185
#> 336 526 1046
#> 337 601 1197
#> 338 326 676
#> 339 0 0
#> 340 242 481
#> 341 330 646
#> 342 0 0
#> 343 0 0
#> 344 0 0
#> 345 0 0
#> 346 153 320
#> 347 617 1227
#> 348 440 869
#> 349 60 127
#> 350 155 306
#> 351 553 1102
#> 352 0 0
#> 353 0 0
#> 354 479 953
#> 355 306 604
#> 356 273 546
#> 357 72 149
#> 358 637 1271
#> 359 0 0
#> 360 218 431
#>
#> $no_purify$moments
#> id mu.ripdr sigma.ripdr mu.ripds sigma.ripds covariance
#> 1 I1 NA NA NA NA NA
#> 2 I2 0 0.03204069 -2.076045e-03 0.009510456 -2.173595e-04
#> 3 I3 0 0.02344779 9.362535e-04 0.008917170 -4.711901e-05
#> 4 I4 NA NA NA NA NA
#> 5 I5 NA NA NA NA NA
#> 6 I6 NA NA NA NA NA
#> 7 I7 NA NA NA NA NA
#> 8 I8 NA NA NA NA NA
#> 9 I9 NA NA NA NA NA
#> 10 I10 0 0.02905728 -2.415769e-03 0.009345260 -1.189033e-04
#> 11 I11 NA NA NA NA NA
#> 12 I12 NA NA NA NA NA
#> 13 I13 0 0.02485799 1.935566e-03 0.010325814 -1.896026e-04
#> 14 I14 0 0.03102668 3.004885e-03 0.010641494 -2.762189e-04
#> 15 I15 0 0.03038520 2.067780e-03 0.009585463 -2.183157e-04
#> 16 I16 NA NA NA NA NA
#> 17 I17 NA NA NA NA NA
#> 18 I18 0 0.02458680 1.805196e-03 0.008614066 -7.286761e-05
#> 19 I19 NA NA NA NA NA
#> 20 I20 0 0.02581164 1.042330e-03 0.012061428 -1.981457e-04
#> 21 I21 NA NA NA NA NA
#> 22 I22 NA NA NA NA NA
#> 23 I23 0 0.02331620 1.973653e-03 0.011754185 -9.936534e-05
#> 24 I24 NA NA NA NA NA
#> 25 I25 0 0.02912978 1.201522e-03 0.008929023 -1.147983e-04
#> 26 I26 0 0.02715884 2.115550e-03 0.011378103 -2.497412e-04
#> 27 I27 NA NA NA NA NA
#> 28 I28 NA NA NA NA NA
#> 29 I29 NA NA NA NA NA
#> 30 I30 NA NA NA NA NA
#> 31 I31 0 0.02432182 3.029463e-03 0.008640477 -9.919811e-05
#> 32 I32 NA NA NA NA NA
#> 33 I33 NA NA NA NA NA
#> 34 I34 NA NA NA NA NA
#> 35 I35 0 0.02479104 -3.855085e-03 0.008687723 -7.964052e-05
#> 36 I36 NA NA NA NA NA
#> 37 I37 NA NA NA NA NA
#> 38 I38 NA NA NA NA NA
#> 39 I39 NA NA NA NA NA
#> 40 I40 NA NA NA NA NA
#> 41 I41 NA NA NA NA NA
#> 42 I42 0 0.03013613 3.833317e-03 0.009632353 -2.114780e-04
#> 43 I43 0 0.02809442 2.965036e-04 0.010785419 -2.130537e-04
#> 44 I44 NA NA NA NA NA
#> 45 I45 NA NA NA NA NA
#> 46 I46 NA NA NA NA NA
#> 47 I47 NA NA NA NA NA
#> 48 I48 NA NA NA NA NA
#> 49 I49 NA NA NA NA NA
#> 50 I50 NA NA NA NA NA
#> 51 I51 NA NA NA NA NA
#> 52 I52 NA NA NA NA NA
#> 53 I53 NA NA NA NA NA
#> 54 I54 NA NA NA NA NA
#> 55 I55 0 0.02749570 3.909583e-03 0.010826443 -2.097052e-04
#> 56 I56 NA NA NA NA NA
#> 57 I57 NA NA NA NA NA
#> 58 I58 0 0.02173160 -6.648170e-03 0.009972358 -9.283878e-05
#> 59 I59 NA NA NA NA NA
#> 60 I60 NA NA NA NA NA
#> 61 I61 0 0.02741816 4.588836e-04 0.009065068 -1.407200e-04
#> 62 I62 0 0.03218557 -4.291317e-03 0.008215086 -1.329844e-04
#> 63 I63 NA NA NA NA NA
#> 64 I64 0 0.02403970 6.849135e-03 0.010271591 -1.830096e-04
#> 65 I65 NA NA NA NA NA
#> 66 I66 NA NA NA NA NA
#> 67 I67 NA NA NA NA NA
#> 68 I68 0 0.03081166 -1.941197e-04 0.009612822 -2.054620e-04
#> 69 I69 0 0.03294005 -3.509948e-03 0.010755252 -2.448460e-04
#> 70 I70 NA NA NA NA NA
#> 71 I71 NA NA NA NA NA
#> 72 I72 NA NA NA NA NA
#> 73 I73 NA NA NA NA NA
#> 74 I74 0 0.02533828 -2.633051e-03 0.009163172 -1.227324e-04
#> 75 I75 0 0.02824170 1.349109e-04 0.009684188 -1.994265e-04
#> 76 I76 NA NA NA NA NA
#> 77 I77 NA NA NA NA NA
#> 78 I78 NA NA NA NA NA
#> 79 I79 NA NA NA NA NA
#> 80 I80 NA NA NA NA NA
#> 81 I81 NA NA NA NA NA
#> 82 I82 NA NA NA NA NA
#> 83 I83 NA NA NA NA NA
#> 84 I84 0 0.03190934 -1.421676e-03 0.008886836 -1.829568e-04
#> 85 I85 NA NA NA NA NA
#> 86 I86 NA NA NA NA NA
#> 87 I87 NA NA NA NA NA
#> 88 I88 NA NA NA NA NA
#> 89 I89 NA NA NA NA NA
#> 90 I90 NA NA NA NA NA
#> 91 I91 NA NA NA NA NA
#> 92 I92 NA NA NA NA NA
#> 93 I93 NA NA NA NA NA
#> 94 I94 NA NA NA NA NA
#> 95 I95 NA NA NA NA NA
#> 96 I96 NA NA NA NA NA
#> 97 I97 0 0.02860182 -8.626546e-04 0.009233684 -1.723690e-04
#> 98 I98 NA NA NA NA NA
#> 99 I99 NA NA NA NA NA
#> 100 I100 NA NA NA NA NA
#> 101 I101 NA NA NA NA NA
#> 102 I102 NA NA NA NA NA
#> 103 I103 NA NA NA NA NA
#> 104 I104 NA NA NA NA NA
#> 105 I105 NA NA NA NA NA
#> 106 I106 NA NA NA NA NA
#> 107 I107 NA NA NA NA NA
#> 108 I108 NA NA NA NA NA
#> 109 I109 NA NA NA NA NA
#> 110 I110 NA NA NA NA NA
#> 111 I111 NA NA NA NA NA
#> 112 I112 NA NA NA NA NA
#> 113 I113 NA NA NA NA NA
#> 114 I114 NA NA NA NA NA
#> 115 I115 NA NA NA NA NA
#> 116 I116 NA NA NA NA NA
#> 117 I117 NA NA NA NA NA
#> 118 I118 NA NA NA NA NA
#> 119 I119 0 0.02943175 -3.247570e-03 0.010030776 -1.761713e-04
#> 120 I120 NA NA NA NA NA
#> 121 I121 NA NA NA NA NA
#> 122 I122 NA NA NA NA NA
#> 123 I123 NA NA NA NA NA
#> 124 I124 NA NA NA NA NA
#> 125 I125 NA NA NA NA NA
#> 126 I126 0 0.02981864 1.356256e-06 0.010007283 -2.129629e-04
#> 127 I127 NA NA NA NA NA
#> 128 I128 NA NA NA NA NA
#> 129 I129 0 0.02555151 -1.558048e-03 0.010097299 -1.089688e-04
#> 130 I130 0 0.03065449 1.773209e-03 0.012744031 -1.587826e-04
#> 131 I131 NA NA NA NA NA
#> 132 I132 NA NA NA NA NA
#> 133 I133 0 0.02619142 1.029408e-03 0.009278095 -1.609547e-04
#> 134 I134 NA NA NA NA NA
#> 135 I135 NA NA NA NA NA
#> 136 I136 NA NA NA NA NA
#> 137 I137 NA NA NA NA NA
#> 138 I138 0 0.02536732 -6.894275e-04 0.009072760 -6.386651e-05
#> 139 I139 NA NA NA NA NA
#> 140 I140 NA NA NA NA NA
#> 141 I141 NA NA NA NA NA
#> 142 I142 NA NA NA NA NA
#> 143 I143 0 0.03051259 -3.878429e-03 0.010107017 -2.003339e-04
#> 144 I144 NA NA NA NA NA
#> 145 I145 0 0.02528121 3.373258e-03 0.009560479 -1.579033e-04
#> 146 I146 0 0.02584523 5.908046e-03 0.009508632 -1.513412e-04
#> 147 I147 0 0.03201054 -1.765162e-03 0.008700655 -1.929237e-04
#> 148 I148 NA NA NA NA NA
#> 149 I149 0 0.02978147 -1.018332e-03 0.008488319 -1.521805e-04
#> 150 I150 NA NA NA NA NA
#> 151 I151 NA NA NA NA NA
#> 152 I152 0 0.02644754 2.530730e-03 0.009375777 -4.593518e-05
#> 153 I153 0 0.02282186 -2.412483e-03 0.009019955 -3.610990e-05
#> 154 I154 NA NA NA NA NA
#> 155 I155 NA NA NA NA NA
#> 156 I156 NA NA NA NA NA
#> 157 I157 NA NA NA NA NA
#> 158 I158 NA NA NA NA NA
#> 159 I159 NA NA NA NA NA
#> 160 I160 NA NA NA NA NA
#> 161 I161 NA NA NA NA NA
#> 162 I162 0 0.02510212 8.514954e-03 0.010631165 -1.950078e-04
#> 163 I163 0 0.02617878 8.849936e-05 0.008216971 -6.716044e-05
#> 164 I164 NA NA NA NA NA
#> 165 I165 NA NA NA NA NA
#> 166 I166 NA NA NA NA NA
#> 167 I167 0 0.02713466 -5.528797e-03 0.009429625 -9.216992e-05
#> 168 I168 0 0.02964984 1.416051e-03 0.011213663 -2.834604e-04
#> 169 I169 NA NA NA NA NA
#> 170 I170 NA NA NA NA NA
#> 171 I171 NA NA NA NA NA
#> 172 I172 NA NA NA NA NA
#> 173 I173 NA NA NA NA NA
#> 174 I174 NA NA NA NA NA
#> 175 I175 NA NA NA NA NA
#> 176 I176 NA NA NA NA NA
#> 177 I177 NA NA NA NA NA
#> 178 I178 NA NA NA NA NA
#> 179 I179 NA NA NA NA NA
#> 180 I180 NA NA NA NA NA
#> 181 I181 0 0.02275765 5.439623e-03 0.009651130 -1.188190e-04
#> 182 I182 NA NA NA NA NA
#> 183 I183 NA NA NA NA NA
#> 184 I184 0 0.02772822 1.493826e-03 0.009405622 -1.714278e-04
#> 185 I185 NA NA NA NA NA
#> 186 I186 NA NA NA NA NA
#> 187 I187 0 0.03285174 -3.586674e-03 0.009321021 -2.137675e-04
#> 188 I188 0 0.02380517 1.297320e-03 0.008910626 -9.972533e-05
#> 189 I189 NA NA NA NA NA
#> 190 I190 NA NA NA NA NA
#> 191 I191 NA NA NA NA NA
#> 192 I192 NA NA NA NA NA
#> 193 I193 NA NA NA NA NA
#> 194 I194 NA NA NA NA NA
#> 195 I195 NA NA NA NA NA
#> 196 I196 NA NA NA NA NA
#> 197 I197 NA NA NA NA NA
#> 198 I198 NA NA NA NA NA
#> 199 I199 0 0.02456717 4.525936e-04 0.009924401 -9.134948e-05
#> 200 I200 NA NA NA NA NA
#> 201 I201 NA NA NA NA NA
#> 202 I202 0 0.02873582 3.260130e-04 0.008382728 -1.203092e-04
#> 203 I203 0 0.02626908 9.785882e-06 0.011247808 -2.477400e-04
#> 204 I204 NA NA NA NA NA
#> 205 I205 NA NA NA NA NA
#> 206 I206 NA NA NA NA NA
#> 207 I207 NA NA NA NA NA
#> 208 I208 NA NA NA NA NA
#> 209 I209 NA NA NA NA NA
#> 210 I210 0 0.02246407 6.754731e-04 0.009530739 -4.289013e-05
#> 211 I211 NA NA NA NA NA
#> 212 I212 NA NA NA NA NA
#> 213 I213 NA NA NA NA NA
#> 214 I214 NA NA NA NA NA
#> 215 I215 0 0.03055590 1.833266e-03 0.008773089 -1.515569e-04
#> 216 I216 NA NA NA NA NA
#> 217 I217 NA NA NA NA NA
#> 218 I218 0 0.03202487 -6.693125e-03 0.010139313 -2.479628e-04
#> 219 I219 NA NA NA NA NA
#> 220 I220 NA NA NA NA NA
#> 221 I221 NA NA NA NA NA
#> 222 I222 NA NA NA NA NA
#> 223 I223 NA NA NA NA NA
#> 224 I224 NA NA NA NA NA
#> 225 I225 NA NA NA NA NA
#> 226 I226 NA NA NA NA NA
#> 227 I227 0 0.02509226 5.260108e-03 0.009414234 -1.289064e-04
#> 228 I228 NA NA NA NA NA
#> 229 I229 0 0.03233981 8.207248e-04 0.007992854 -1.739364e-04
#> 230 I230 NA NA NA NA NA
#> 231 I231 0 0.02602342 2.868258e-03 0.010213519 -1.950373e-04
#> 232 I232 NA NA NA NA NA
#> 233 I233 NA NA NA NA NA
#> 234 I234 NA NA NA NA NA
#> 235 I235 0 0.02881807 -1.240722e-03 0.009502292 -1.809035e-04
#> 236 I236 0 0.02495742 1.084274e-03 0.009541390 -1.584512e-04
#> 237 I237 0 0.02838632 1.800769e-03 0.007896576 -1.053738e-04
#> 238 I238 NA NA NA NA NA
#> 239 I239 NA NA NA NA NA
#> 240 I240 NA NA NA NA NA
#> 241 I241 NA NA NA NA NA
#> 242 I242 0 0.03089369 2.941384e-03 0.007658513 -1.464107e-04
#> 243 I243 NA NA NA NA NA
#> 244 I244 0 0.02638811 -1.159366e-04 0.010125062 -1.912377e-04
#> 245 I245 NA NA NA NA NA
#> 246 I246 0 0.02288103 -2.647282e-03 0.009195894 -9.935365e-05
#> 247 I247 NA NA NA NA NA
#> 248 I248 0 0.02881074 2.339678e-03 0.012157112 -2.954805e-04
#> 249 I249 0 0.02882522 2.665285e-03 0.009896649 -8.454379e-05
#> 250 I250 0 0.02618714 -3.432173e-05 0.010779602 -1.722987e-04
#> 251 I251 NA NA NA NA NA
#> 252 I252 0 0.02306011 -1.600690e-03 0.009695681 -1.198477e-04
#> 253 I253 0 0.03054304 -2.619177e-03 0.008212364 -9.952792e-05
#> 254 I254 NA NA NA NA NA
#> 255 I255 NA NA NA NA NA
#> 256 I256 NA NA NA NA NA
#> 257 I257 NA NA NA NA NA
#> 258 I258 NA NA NA NA NA
#> 259 I259 NA NA NA NA NA
#> 260 I260 NA NA NA NA NA
#> 261 I261 0 0.02831756 4.733343e-03 0.011506042 -2.827281e-04
#> 262 I262 NA NA NA NA NA
#> 263 I263 NA NA NA NA NA
#> 264 I264 NA NA NA NA NA
#> 265 I265 NA NA NA NA NA
#> 266 I266 NA NA NA NA NA
#> 267 I267 NA NA NA NA NA
#> 268 I268 NA NA NA NA NA
#> 269 I269 NA NA NA NA NA
#> 270 I270 0 0.03028471 -3.687516e-04 0.011982856 -2.915029e-04
#> 271 I271 NA NA NA NA NA
#> 272 I272 0 0.02687703 -3.013844e-04 0.009797497 -1.786352e-04
#> 273 I273 NA NA NA NA NA
#> 274 I274 NA NA NA NA NA
#> 275 I275 NA NA NA NA NA
#> 276 I276 0 0.02777167 3.542759e-03 0.009358594 -1.774687e-04
#> 277 I277 0 0.03125571 1.860290e-03 0.010211796 -2.513256e-04
#> 278 I278 NA NA NA NA NA
#> 279 I279 NA NA NA NA NA
#> 280 I280 NA NA NA NA NA
#> 281 I281 NA NA NA NA NA
#> 282 I282 NA NA NA NA NA
#> 283 I283 NA NA NA NA NA
#> 284 I284 NA NA NA NA NA
#> 285 I285 NA NA NA NA NA
#> 286 I286 NA NA NA NA NA
#> 287 I287 NA NA NA NA NA
#> 288 I288 NA NA NA NA NA
#> 289 I289 NA NA NA NA NA
#> 290 I290 NA NA NA NA NA
#> 291 I291 NA NA NA NA NA
#> 292 I292 NA NA NA NA NA
#> 293 I293 NA NA NA NA NA
#> 294 I294 NA NA NA NA NA
#> 295 I295 NA NA NA NA NA
#> 296 I296 0 0.02443548 7.746534e-03 0.009398311 -5.177503e-05
#> 297 I297 NA NA NA NA NA
#> 298 I298 0 0.02314426 2.985163e-03 0.008848456 -5.655551e-05
#> 299 I299 NA NA NA NA NA
#> 300 I300 0 0.02659143 2.653743e-03 0.008854874 -9.176503e-05
#> 301 I301 NA NA NA NA NA
#> 302 I302 NA NA NA NA NA
#> 303 I303 NA NA NA NA NA
#> 304 I304 NA NA NA NA NA
#> 305 I305 NA NA NA NA NA
#> 306 I306 0 0.02916031 5.868138e-03 0.013575330 -1.534402e-04
#> 307 I307 NA NA NA NA NA
#> 308 I308 NA NA NA NA NA
#> 309 I309 NA NA NA NA NA
#> 310 I310 0 0.02762762 8.072106e-04 0.010552075 -1.926663e-04
#> 311 I311 0 0.03152270 -1.436560e-03 0.010616772 -2.377873e-04
#> 312 I312 0 0.02720834 1.722008e-03 0.012295545 -1.541401e-04
#> 313 I313 NA NA NA NA NA
#> 314 I314 NA NA NA NA NA
#> 315 I315 NA NA NA NA NA
#> 316 I316 NA NA NA NA NA
#> 317 I317 NA NA NA NA NA
#> 318 I318 NA NA NA NA NA
#> 319 I319 NA NA NA NA NA
#> 320 I320 NA NA NA NA NA
#> 321 I321 NA NA NA NA NA
#> 322 I322 0 0.02464714 -1.084342e-03 0.009734318 -1.451632e-04
#> 323 I323 NA NA NA NA NA
#> 324 I324 NA NA NA NA NA
#> 325 I325 0 0.02498683 3.759896e-03 0.009504020 -1.443816e-04
#> 326 I326 NA NA NA NA NA
#> 327 I327 0 0.02853970 8.713848e-04 0.010481394 -2.350467e-04
#> 328 I328 NA NA NA NA NA
#> 329 I329 NA NA NA NA NA
#> 330 I330 NA NA NA NA NA
#> 331 I331 0 0.02940438 3.352529e-03 0.009227865 -1.284304e-04
#> 332 I332 NA NA NA NA NA
#> 333 I333 NA NA NA NA NA
#> 334 I334 0 0.02451207 5.583847e-04 0.009003879 -1.077428e-04
#> 335 I335 NA NA NA NA NA
#> 336 I336 0 0.02927795 1.498506e-03 0.007755029 -9.004692e-05
#> 337 I337 0 0.02548221 5.242267e-04 0.009986078 -1.569593e-04
#> 338 I338 NA NA NA NA NA
#> 339 I339 NA NA NA NA NA
#> 340 I340 NA NA NA NA NA
#> 341 I341 NA NA NA NA NA
#> 342 I342 NA NA NA NA NA
#> 343 I343 NA NA NA NA NA
#> 344 I344 NA NA NA NA NA
#> 345 I345 NA NA NA NA NA
#> 346 I346 NA NA NA NA NA
#> 347 I347 0 0.02574975 8.663063e-04 0.009380317 -1.555430e-04
#> 348 I348 NA NA NA NA NA
#> 349 I349 NA NA NA NA NA
#> 350 I350 NA NA NA NA NA
#> 351 I351 0 0.02675801 -2.563496e-03 0.010288179 -1.577419e-04
#> 352 I352 NA NA NA NA NA
#> 353 I353 NA NA NA NA NA
#> 354 I354 0 0.02957798 -2.592826e-03 0.010386070 -2.078090e-04
#> 355 I355 NA NA NA NA NA
#> 356 I356 NA NA NA NA NA
#> 357 I357 NA NA NA NA NA
#> 358 I358 0 0.02547355 -2.427927e-03 0.008226364 -9.772859e-06
#> 359 I359 NA NA NA NA NA
#> 360 I360 NA NA NA NA NA
#>
#> $no_purify$ipd_item
#> $no_purify$ipd_item$ripdr
#> [1] 20 26 42 55 58 97 129 130 138 145 149 181 184 203 215 231 242 246 252
#> [20] 277 310 312 334 336 351
#>
#> $no_purify$ipd_item$ripds
#> [1] 20 26 130 184 215 236 277 358
#>
#> $no_purify$ipd_item$ripdrs
#> [1] 26 55 58 97 129 130 138 145 149 181 184 203 215 231 236 242 246 252 277
#> [20] 310 312 334 336 351 354
#>
#>
#> $no_purify$score
#> [1] -4.516881e-01 4.129546e-01 -1.884870e+00 -1.330220e+00 1.790494e+00
#> [6] -1.778357e-01 2.550170e+00 1.389985e-01 8.366753e-01 -1.807742e-01
#> [11] -2.400741e-01 -3.322413e-01 3.427514e-02 4.248568e-02 4.785248e-01
#> [16] 4.131119e-01 -4.431497e-01 -3.809656e-01 2.218231e-01 4.524347e-01
#> [21] 1.209503e+00 6.059516e-01 -3.227264e-01 -1.920591e+00 1.062187e-01
#> [26] 6.884000e-01 -1.314468e+00 -3.582888e-01 -5.247735e-01 -1.888175e+00
#> [31] -1.867107e-01 -4.959585e-01 1.519656e+00 1.227128e+00 -1.389466e+00
#> [36] -7.628738e-01 2.495060e-01 -6.612952e-01 3.440489e-01 4.528921e-01
#> [41] 9.546515e-01 -1.328193e+00 1.254966e+00 5.145359e-02 -1.593000e+00
#> [46] 1.301038e+00 -6.530621e-01 -9.007484e-01 -1.177012e+00 -7.093921e-01
#> [51] -2.170935e+00 8.165357e-01 2.518764e+00 -2.223026e+00 -1.016537e-01
#> [56] 3.297652e-01 -6.688115e-01 -1.359709e-01 -1.009270e-01 -1.639101e-02
#> [61] 2.239016e+00 -2.803089e-01 -1.662974e-02 -5.476189e-01 -3.791693e-01
#> [66] 2.031266e-01 -2.028910e+00 -9.412185e-01 9.599352e-01 -1.088217e+00
#> [71] 8.160381e-01 1.873484e-01 5.989573e-02 5.275391e-01 1.316276e+00
#> [76] 2.477746e-01 -2.099500e+00 3.879685e-01 1.986302e+00 3.659204e-01
#> [81] 2.956493e+00 8.982388e-01 -2.586514e-01 -1.971450e+00 -1.416526e+00
#> [86] -1.144445e+00 5.080965e-02 1.641485e+00 -1.904175e+00 -9.830322e-01
#> [91] -2.867183e+00 -6.139342e-01 1.179942e+00 1.100630e+00 -5.732537e-01
#> [96] 1.535418e-01 9.353234e-01 -1.072041e+00 7.082611e-02 -2.973231e-01
#> [101] 1.940411e+00 1.841320e+00 -5.144709e-01 -9.811592e-01 -1.053322e+00
#> [106] 1.055137e+00 -1.246642e+00 1.437399e+00 -2.503546e+00 -4.813641e-01
#> [111] -1.907695e+00 9.207981e-01 1.015540e+00 -7.182049e-01 -2.324051e-01
#> [116] 7.792903e-02 -9.835509e-01 -2.784007e+00 -9.748600e-01 8.557050e-02
#> [121] 6.928651e-01 -8.429458e-01 2.195906e+00 -1.116394e+00 -1.130983e+00
#> [126] 1.043427e-01 -1.328676e+00 2.571097e+00 -8.924512e-02 1.776333e-01
#> [131] -3.738824e-01 1.659942e+00 -9.882730e-01 7.975685e-01 3.192156e-02
#> [136] -7.298580e-01 6.636822e-01 -1.199308e+00 4.855810e-01 5.867169e-01
#> [141] -9.239430e-01 4.978267e-01 8.146926e-01 -4.609562e-01 -2.836956e-01
#> [146] -1.438529e+00 2.773628e+00 -1.374819e+00 5.778535e-01 1.627050e+00
#> [151] -5.397222e-01 2.055349e+00 -8.533472e-01 1.954799e+00 2.399638e-01
#> [156] 2.560735e-01 1.531815e+00 1.407198e+00 5.642872e-01 1.537853e+00
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#> [1906] -4.974289e-01 1.174730e-01 -1.102817e+00 -4.057302e-01 6.713573e-01
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#> [1936] 1.739076e+00 1.709098e+00 1.593352e-01 6.175442e-01 8.165295e-01
#> [1941] 1.366008e-02 1.571472e+00 -1.161892e+00 3.236269e-01 1.005158e+00
#> [1946] -1.096013e+00 -2.993742e-01 9.507548e-01 1.730216e+00 -3.127679e-02
#> [1951] 1.909429e-01 -5.682177e-01 1.349781e+00 4.140098e-01 -1.066585e+00
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#> [1966] 7.404356e-01 -5.897145e-01 1.842194e+00 1.097875e+00 -9.801224e-01
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#> [1976] -8.416914e-01 5.662638e-01 -1.286745e-01 5.113569e-01 8.406327e-01
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#> [5166] -1.033283e+00 -2.893532e-01 7.088371e-01 -7.581610e-01 1.472536e+00
#> [5171] 3.068633e-01 5.436298e-01 4.517924e-01 -1.146898e+00 1.377295e-01
#> [5176] -2.922764e-01 -6.973318e-01 -3.337287e-01 -4.143669e-01 2.090301e-01
#> [5181] -2.350621e-02 1.392982e+00 1.905816e+00 -7.165784e-01 4.029917e-01
#> [5186] 8.997945e-01 -1.707152e-01 5.318299e-01 -8.569836e-02 4.649801e-01
#> [5191] -1.096396e+00 -1.611802e+00 -7.022984e-01 -5.687615e-01 1.750582e-01
#> [5196] -1.717684e-01 -1.369797e+00 5.403217e-01 -9.341924e-01 -9.611064e-02
#> [5201] 1.435740e+00 1.074713e+00 -8.038727e-01 9.193664e-01 2.598545e+00
#> [5206] -2.519782e+00 7.759103e-01 -3.812235e-02 1.204824e+00 7.422604e-01
#> [5211] 1.148897e-01 1.004854e+00 4.947169e-01 1.137205e+00 -1.283170e+00
#> [5216] 5.736154e-01 2.016942e+00 9.713394e-01 -4.008396e-01 9.759482e-01
#> [5221] -7.377811e-01 4.454252e-01 1.212614e+00 1.180957e+00 -2.692828e-01
#> [5226] 9.472518e-03 -1.827695e+00 4.090735e-01 -2.043965e-01 1.078003e+00
#> [5231] 5.486197e-03 -1.532548e+00 1.096338e-01 2.319845e-01 1.647744e+00
#> [5236] 1.468691e+00 -6.452634e-01 2.635202e-01 -9.326561e-02 -8.664334e-01
#> [5241] -9.692589e-01 -1.358644e-01 -8.507578e-01 -1.377603e-01 -6.583896e-01
#> [5246] -1.580636e+00 -7.635310e-01 -2.454751e+00 -6.976596e-01 -9.741567e-01
#> [5251] -1.140659e+00 -1.524881e-01 -2.783013e-01 -1.434255e+00 -2.325035e-01
#> [5256] 1.612277e+00 2.868889e-01 1.523384e+00 1.969226e+00 -3.642184e+00
#> [5261] -5.579350e-01 -2.829567e+00 9.428300e-02 4.609910e-01 -1.440130e-01
#> [5266] 1.964118e+00 5.037551e-01 1.341066e+00 -9.496825e-01 -1.489858e+00
#> [5271] 5.429438e-01 -6.675061e-01 -5.963086e-01 -5.513063e-01 6.801017e-01
#> [5276] 7.160299e-01 1.500846e+00 2.430120e-01 7.743687e-01 2.052865e-01
#> [5281] -1.392403e+00 5.448456e-01 2.052933e-01 -6.023570e-01 -1.982240e+00
#> [5286] -1.243019e-01 -1.160801e+00 -3.442169e-01 -7.391523e-02 6.256793e-01
#> [5291] 9.153881e-01 -1.020577e+00 5.857860e-01 -2.374892e-01 6.264543e-01
#> [5296] 3.885844e-01 -8.266410e-01 -2.251685e+00 1.929957e-01 -1.277210e+00
#> [5301] 2.141019e-01 5.254685e-01 -6.016118e-01 9.376527e-02 -8.249039e-01
#> [5306] -5.320884e-01 -9.967996e-01 -1.407460e-01 3.563946e+00 4.997821e-01
#> [5311] 7.351288e-01 -9.597822e-01 -5.790302e-01 7.137313e-01 -9.628631e-01
#> [5316] 1.136065e+00 -1.574929e-01 8.190181e-02 -9.026428e-01 5.427228e-01
#> [5321] -1.666358e-01 -1.125462e+00 -7.042927e-01 1.726361e+00 1.373602e-01
#> [5326] -3.056262e-01 1.207172e+00 -1.098433e-01 -2.063791e+00 -2.728072e+00
#> [5331] 7.636306e-01 -2.143111e+00 -2.155152e-01 8.618079e-01 -1.459049e-01
#> [5336] -2.743059e-01 -9.320855e-01 -7.954671e-01 4.532004e-01 -1.122703e+00
#> [5341] 5.690318e-01 -2.801897e-01 -3.001545e+00 -1.116311e+00 7.406261e-01
#> [5346] -3.062799e-01 7.945030e-01 2.634549e-01 -1.938087e+00 -6.739889e-02
#> [5351] 6.454273e-01 -6.699084e-01 -1.372932e+00 5.696168e-02 -6.958797e-01
#> [5356] 1.245701e+00 -4.232799e-01 -4.912670e-01 8.168497e-01 -3.539763e-01
#> [5361] -2.364178e+00 -4.298509e-01 5.493889e-01 1.009399e+00 -7.199201e-01
#> [5366] -2.053492e+00 5.823633e-01 8.686352e-02 1.075358e+00 8.305806e-01
#> [5371] 6.450397e-02 6.590146e-01 6.274287e-01 -5.465457e-01 -1.767858e+00
#> [5376] 2.763242e-01 -5.149803e-01 1.191430e+00 4.372842e-01 -1.697459e+00
#> [5381] -5.223516e-01 -6.831220e-01 1.107253e+00 3.685722e-01 7.672324e-01
#> [5386] 8.576683e-01 -4.927447e-01 3.947856e+00 -3.528797e-01 1.061869e+00
#> [5391] 1.580964e+00 8.610284e-01 -7.959911e-01 -9.345805e-01 3.224704e-03
#> [5396] 5.141292e-01 -7.782410e-01 1.304620e+00 8.293233e-01 -3.387786e+00
#> [5401] 9.271635e-01 -1.026928e+00 7.730809e-01 -1.562442e-01 -6.070829e-01
#> [5406] 2.480802e-01 -1.031035e-01 -2.629385e+00 -1.367270e+00 8.840886e-01
#> [5411] 1.016304e+00 -5.003985e-01 -7.359901e-01 -2.051397e+00 -2.352648e+00
#> [5416] -2.052868e+00 2.638174e-01 -5.807026e-01 -2.327972e-01 -1.262566e+00
#> [5421] 3.429074e-01 1.419236e+00 -3.007735e-01 -3.444419e+00 -1.106900e+00
#> [5426] 1.015189e+00 1.517940e+00 2.765057e-01 1.640225e+00 8.500375e-01
#> [5431] -4.446388e-01 8.470665e-01 -7.584833e-01 -6.060575e-01 3.046132e-01
#> [5436] -2.175034e+00 -1.748489e-02 3.376842e-03 8.611043e-01 8.443904e-01
#> [5441] 1.939458e-01 8.743764e-02 -4.998442e-01 -1.501398e-01 -3.334617e-01
#> [5446] 6.943819e-01 -8.585221e-02 7.670856e-01 -1.099170e+00 -3.878252e-01
#> [5451] 2.227110e+00 1.077540e+00 -4.572469e-01 9.762239e-01 1.563353e+00
#> [5456] 3.336729e-01 -3.059895e-01 -1.271558e+00 3.437086e-02 -5.064310e-03
#> [5461] 5.274498e-01 -1.199811e-03 -6.251476e-01 -7.913354e-01 -1.802583e+00
#> [5466] -8.917415e-02 -8.746792e-01 -2.291412e-02 2.041242e-01 4.892028e-01
#> [5471] -1.138758e-01 1.314660e+00 2.212439e-01 -1.426052e+00 9.533689e-01
#> [5476] 8.908382e-01 -6.832231e-01 6.677101e-01 -2.051331e+00 1.037906e+00
#> [5481] 9.356322e-03 1.080118e+00 2.872928e-01 2.121370e+00 -7.369150e-01
#> [5486] -1.459354e+00 4.717368e-01 -8.994181e-01 3.301641e-01 -1.180774e-01
#> [5491] -1.043014e+00 6.510240e-01 1.052826e+00 6.728730e-01 -2.396341e-01
#> [5496] 3.519948e-02 -1.143113e-01 -6.333603e-01 -1.635509e+00 5.937237e-01
#> [5501] -1.792892e+00 -8.973004e-02 -2.227884e-02 -8.440712e-01 7.103116e-02
#> [5506] -2.366472e+00 -1.512957e-01 1.626337e-01 -5.639949e-02 1.283758e-02
#> [5511] 1.167944e+00 -2.640735e+00 4.918240e-01 -3.692810e-01 -2.356009e+00
#> [5516] -3.079352e-01 7.446921e-01 5.978406e-02 -7.559336e-01 6.203189e-01
#> [5521] -1.331073e-01 7.765751e-02 1.182751e+00 -7.839111e-01 -1.286348e+00
#> [5526] -2.851610e+00 8.045890e-01 2.002358e+00 -2.106460e-01 6.698399e-01
#> [5531] 2.198085e+00 1.718853e+00 -1.914766e+00 3.083140e-01 1.104565e+00
#> [5536] 4.958741e-01 2.488998e+00 -1.216905e-01 1.355637e+00 9.844978e-01
#> [5541] 1.673818e+00 2.825264e-01 1.877701e+00 -9.836232e-01 -8.869252e-01
#> [5546] 6.151060e-01 -5.856547e-01 1.112287e+00 1.522514e+00 8.728327e-02
#> [5551] 2.108118e-01 1.088760e+00 4.321221e-01 1.860644e+00 -1.238029e+00
#> [5556] 3.860116e-01 -7.483135e-01 -5.631461e-01 -1.520048e+00 5.139716e-01
#> [5561] -9.673907e-01 -1.331033e-01 -6.930458e-01 -1.136505e+00 -2.732503e+00
#> [5566] 1.728255e+00 -1.532211e+00 -4.480989e-01 1.711167e-01 9.755668e-01
#> [5571] -1.166688e+00 -3.526195e-01 6.273751e-01 9.611859e-01 -2.906171e+00
#> [5576] -2.790175e-02 2.879840e+00 5.261557e-01 -1.734368e+00 1.798726e+00
#> [5581] -4.453985e-01 8.760228e-02 -1.302470e-01 9.752540e-01 1.481227e-01
#> [5586] -4.536736e-01 -5.150422e-01 -3.924893e-01 5.618122e-01 9.520692e-01
#> [5591] 3.509195e-01 -1.319495e-03 -9.510082e-01 1.113573e+00 3.068296e-01
#> [5596] -2.833310e-01 3.267724e-01 -1.193034e+00 -2.372305e+00 -1.555191e+00
#> [5601] -1.090741e+00 6.162163e-02 -3.624787e-02 1.178399e+00 -1.958613e-01
#> [5606] -4.251067e-01 -4.934096e-01 -6.252909e-01 -9.305158e-01 1.193604e+00
#> [5611] -1.443543e+00 7.247619e-01 1.029507e+00 -7.223469e-02 -1.981013e-01
#> [5616] 1.886591e+00 8.600782e-01 -6.677077e-01 1.882504e+00 -9.995810e-01
#> [5621] 3.478402e-01 -1.463784e+00 1.786601e+00 2.185698e+00 2.309543e-01
#> [5626] 4.834031e-01 -3.485784e-01 -1.868049e+00 -2.091456e-01 4.211939e-01
#> [5631] 2.076106e-01 5.908277e-01 -2.020022e-01 3.059991e-01 6.551721e-01
#> [5636] -3.051817e-02 1.029219e+00 1.558828e+00 -2.083569e-01 1.985634e+00
#> [5641] -2.445967e-01 1.333625e+00 5.398089e-01 -7.010139e-02 1.008335e-01
#> [5646] -1.384380e-01 -5.975463e-01 -5.248365e-01 -3.109538e-05 3.834552e-02
#> [5651] 1.994222e-01 1.009558e+00 2.011273e+00 1.856214e+00 -1.746132e+00
#> [5656] -3.464308e+00 -5.715702e-01 3.380113e-01 1.859214e+00 1.448120e+00
#> [5661] 2.034742e+00 1.106115e+00 1.259111e+00 -2.197602e+00 -5.890974e-01
#> [5666] -2.027509e+00 2.128043e+00 4.219659e-01 -1.004827e-01 -5.722934e-03
#> [5671] -6.135688e-01 3.067365e+00 -6.159026e-01 1.298811e+00 -3.624651e-01
#> [5676] 8.794420e-01 -6.365842e-01 7.881913e-01 -2.458268e+00 -1.068068e-01
#> [5681] 1.513468e+00 1.829424e+00 -4.787323e-01 9.977422e-01 8.933278e-01
#> [5686] 6.159105e-01 -2.599942e-01 -2.315316e-01 6.230310e-01 7.428258e-01
#> [5691] 5.504230e-01 -2.419519e-01 -1.297650e-01 -3.250985e-01 -1.288768e-01
#> [5696] 2.030790e-01 -5.655247e-01 -1.114632e-01 1.562921e+00 8.215391e-01
#> [5701] -1.070775e-01 2.303222e+00 9.125928e-01 -1.358040e+00 2.351172e+00
#> [5706] -3.324679e-01 -6.513081e-01 -9.118842e-01 -2.552541e+00 1.223272e+00
#> [5711] -1.713817e-01 -1.159187e-01 -5.391394e-01 -1.242874e-01 4.331754e-01
#> [5716] 1.266777e-01 -2.344289e+00 1.149261e+00 6.954560e-01 4.255962e-01
#> [5721] 1.780352e+00 -7.459284e-01 -5.207962e-01 -6.276748e-01 1.605388e+00
#> [5726] 7.348847e-01 -4.249277e-01 -1.791843e+00 8.954192e-01 7.841190e-01
#> [5731] 7.073507e-01 -1.825034e+00 -8.651232e-02 -3.405163e-01 2.506732e-01
#> [5736] 6.419573e-03 2.905538e+00 -1.600864e+00 1.397518e+00 -1.014867e-03
#> [5741] -2.666682e+00 -2.358997e-01 6.372369e-02 2.433329e+00 6.016354e-01
#> [5746] 4.098261e-01 9.181026e-01 -3.312460e-01 1.361098e+00 2.438434e-02
#> [5751] -7.150378e-01 -1.957919e+00 -9.010619e-01 1.114119e+00 2.996030e-01
#> [5756] -1.626077e+00 1.331507e+00 2.874858e-02 3.038192e-01 -6.400609e-02
#> [5761] 3.679738e-01 1.093701e+00 -9.746013e-01 1.781941e+00 1.207821e+00
#> [5766] -4.046506e-02 -3.388970e-01 -2.059708e-01 2.591472e-02 -3.708399e-02
#> [5771] -3.757608e-01 -4.206308e-01 -2.009411e-01 1.334156e+00 8.453159e-01
#> [5776] -3.172051e-01 -3.008231e-01 -2.492082e-01 -5.082597e-01 9.055783e-01
#> [5781] 1.195065e+00 -1.542285e+00 -1.396208e+00 8.751218e-01 -1.011034e+00
#> [5786] 4.378837e-01 -7.117308e-01 1.198739e+00 -1.652258e-01 -3.059371e+00
#> [5791] 1.073549e+00 4.109180e-01 1.215148e+00 2.511272e-02 6.185667e-01
#> [5796] -1.925797e-01 4.389207e-01 -1.861408e+00 6.895565e-01 -3.987394e-01
#> [5801] -6.767241e-01 -2.787559e-01 -5.852290e-02 9.479087e-01 -1.508809e+00
#> [5806] 1.335630e+00 1.238124e+00 -6.875364e-02 3.628812e-01 -1.973941e+00
#> [5811] -1.683910e+00 1.906319e-01 -9.887066e-01 -1.060479e+00 9.792207e-01
#> [5816] -1.103034e-01 7.105243e-01 -4.399341e-01 -1.004633e-01 -5.097872e-01
#> [5821] -2.118987e-01 -4.952091e-01 -2.733433e-01 -4.925389e-01 8.389111e-01
#> [5826] 1.648940e-01 -7.115948e-01 1.532454e+00 2.401232e+00 8.201428e-01
#> [5831] -3.932342e-01 -2.755481e-01 1.821321e+00 2.223558e-01 -6.284746e-01
#> [5836] 1.540380e+00 -1.940328e-01 8.445891e-01 1.652688e+00 -3.639670e-01
#> [5841] 7.239945e-02 3.156870e-01 7.644217e-01 7.063058e-03 -7.605653e-01
#> [5846] -7.163866e-01 4.824207e-01 -1.272478e+00 -1.184460e+00 -5.659173e-01
#> [5851] 9.493661e-01 -1.045135e+00 8.036100e-01 9.940084e-01 1.274907e+00
#> [5856] 1.823147e+00 1.676099e+00 -1.573113e-01 -3.111292e-01 -7.859382e-01
#> [5861] 1.616451e+00 -9.631058e-01 8.230710e-02 -1.327162e+00 5.307041e-01
#> [5866] 3.686792e-01 2.559070e-01 1.514459e+00 -6.633814e-01 4.399471e-03
#> [5871] 1.308776e+00 -1.878243e+00 9.466537e-02 4.068532e-01 1.146452e+00
#> [5876] -2.120977e-01 3.628395e-01 1.703575e+00 -3.029643e-02 1.742583e+00
#> [5881] 4.819860e-02 8.743063e-02 -2.862351e-01 1.036108e+00 -1.180684e-01
#> [5886] 1.448466e-01 -1.339572e+00 1.748957e+00 -6.777318e-01 7.708718e-01
#> [5891] -7.992149e-01 1.028347e-01 -3.424355e-01 -1.067705e+00 1.412075e+00
#> [5896] 2.341518e+00 -7.638171e-01 1.289368e-01 2.592087e+00 5.743455e-01
#> [5901] 3.419929e-01 -3.980108e-01 1.261043e+00 -1.363716e+00 -1.450186e-01
#> [5906] 1.866361e+00 6.246813e-01 6.697948e-01 -1.431015e+00 6.243247e-02
#> [5911] 8.463512e-01 -8.590163e-01 3.692521e-01 -5.075006e-01 5.435322e-02
#> [5916] 1.470350e-02 -7.543808e-01 -2.443094e-01 -7.345594e-01 8.470595e-01
#> [5921] 9.053280e-01 4.897406e-01 1.274568e+00 6.890202e-01 5.908854e-01
#> [5926] -3.495798e-01 1.731029e+00 -1.756068e+00 -1.366491e-01 6.331540e-01
#> [5931] 9.131850e-01 8.161960e-01 4.713879e-02 -4.107797e-02 9.992384e-01
#> [5936] 2.804544e-01 -1.268432e+00 1.138833e+00 1.226836e+00 2.523053e-01
#> [5941] -5.481947e-01 8.029550e-01 2.136545e-02 -1.084524e+00 -7.550954e-01
#> [5946] -9.070223e-01 1.168057e+00 -3.078470e-01 -1.633174e+00 -1.482575e+00
#> [5951] 3.319818e-01 -4.237369e-03 -1.357730e+00 5.436832e-01 4.294403e-02
#> [5956] -3.411628e-01 -1.214328e-01 5.203871e-01 -1.301396e+00 -9.430144e-01
#> [5961] 3.188548e-01 -6.271272e-01 -1.311107e-01 -9.807140e-01 1.983160e+00
#> [5966] 1.007939e-02 5.352400e-01 1.984629e-01 -1.753125e-01 1.579531e+00
#> [5971] 2.172871e-01 -1.302968e-01 -3.080388e-01 9.736363e-01 6.847425e-01
#> [5976] -2.060358e+00 1.357825e+00 -7.848402e-01 1.115146e+00 -2.204296e-01
#> [5981] 9.808066e-01 2.648993e-02 -3.048963e-02 5.940868e-01 1.287500e+00
#> [5986] -1.546677e-01 -1.061446e-01 -1.526580e+00 -9.514096e-01 5.297020e-02
#> [5991] 1.179022e-01 1.088049e+00 -6.185447e-01 -7.832804e-01 6.897931e-01
#> [5996] 6.903034e-01 4.090276e-01 -1.083097e+00 7.957357e-01 -3.233387e-01
#>
#>
#> $purify
#> [1] TRUE
#>
#> $with_purify
#> $with_purify$purify.by
#> [1] "ripdrs"
#>
#> $with_purify$ipd_stat
#> id ripdr z.ripdr ripds z.ripds ripdrs p.ripdr p.ripds p.ripdrs n.ref
#> 1 I1 NA NA NA NA NA NA NA NA 2
#> 2 I2 0.0480 1.5006 -0.0133 -1.7265 3.2831 0.1335 0.0843 0.1937 429
#> 3 I3 0.0451 1.9290 -0.0072 -0.8505 3.9709 0.0537 0.3951 0.1373 698
#> 4 I4 NA NA NA NA NA NA NA NA 221
#> 5 I5 NA NA NA NA NA NA NA NA 85
#> 6 I6 NA NA NA NA NA NA NA NA 61
#> 7 I7 NA NA NA NA NA NA NA NA 104
#> 8 I8 NA NA NA NA NA NA NA NA 179
#> 9 I9 NA NA NA NA NA NA NA NA 19
#> 10 I10 -0.0195 -0.6720 0.0123 1.4655 2.1542 0.5016 0.1428 0.3406 510
#> 11 I11 NA NA NA NA NA NA NA NA 176
#> 12 I12 NA NA NA NA NA NA NA NA 0
#> 13 I13 0.0578 2.3133 0.0068 -0.4360 7.7476 0.0207 0.6628 0.0208 596
#> 14 I14 0.0045 0.1453 0.0013 -0.7124 0.8269 0.8845 0.4762 0.6613 442
#> 15 I15 -0.0068 -0.2220 -0.0038 -0.9270 2.0877 0.8243 0.3539 0.3521 472
#> 16 I16 NA NA NA NA NA NA NA NA 21
#> 17 I17 NA NA NA NA NA NA NA NA 0
#> 18 I18 0.0342 1.3958 0.0092 0.8870 3.7621 0.1628 0.3751 0.1524 664
#> 19 I19 NA NA NA NA NA NA NA NA 0
#> 20 I20 -0.0252 -0.9689 0.0217 0.8486 1.0424 0.3326 0.3961 0.5938 520
#> 21 I21 NA NA NA NA NA NA NA NA 114
#> 22 I22 NA NA NA NA NA NA NA NA 0
#> 23 I23 0.0025 0.1046 0.0164 0.3764 0.2009 0.9167 0.7066 0.9044 583
#> 24 I24 NA NA NA NA NA NA NA NA 0
#> 25 I25 0.0667 2.2987 0.0016 -0.5270 5.3630 0.0215 0.5982 0.0685 506
#> 26 I26 0.1140 4.1845 -0.0310 -3.4234 17.6029 0.0000 0.0006 0.0002 515
#> 27 I27 NA NA NA NA NA NA NA NA 0
#> 28 I28 NA NA NA NA NA NA NA NA 83
#> 29 I29 NA NA NA NA NA NA NA NA 27
#> 30 I30 NA NA NA NA NA NA NA NA 0
#> 31 I31 0.0096 0.3943 -0.0076 -1.3413 1.8080 0.6934 0.1798 0.4049 672
#> 32 I32 NA NA NA NA NA NA NA NA 0
#> 33 I33 NA NA NA NA NA NA NA NA 351
#> 34 I34 NA NA NA NA NA NA NA NA 0
#> 35 I35 0.0222 0.8968 -0.0231 -2.2088 4.9119 0.3698 0.0272 0.0858 656
#> 36 I36 NA NA NA NA NA NA NA NA 67
#> 37 I37 NA NA NA NA NA NA NA NA 69
#> 38 I38 NA NA NA NA NA NA NA NA 136
#> 39 I39 NA NA NA NA NA NA NA NA 145
#> 40 I40 NA NA NA NA NA NA NA NA 107
#> 41 I41 NA NA NA NA NA NA NA NA 69
#> 42 I42 0.1009 3.3477 -0.0010 -1.0994 13.3696 0.0008 0.2716 0.0012 474
#> 43 I43 -0.0084 -0.2989 0.0058 0.3076 0.1096 0.7650 0.7584 0.9467 508
#> 44 I44 NA NA NA NA NA NA NA NA 0
#> 45 I45 NA NA NA NA NA NA NA NA 63
#> 46 I46 NA NA NA NA NA NA NA NA 186
#> 47 I47 NA NA NA NA NA NA NA NA 0
#> 48 I48 NA NA NA NA NA NA NA NA 382
#> 49 I49 NA NA NA NA NA NA NA NA 219
#> 50 I50 NA NA NA NA NA NA NA NA 0
#> 51 I51 NA NA NA NA NA NA NA NA 321
#> 52 I52 NA NA NA NA NA NA NA NA 324
#> 53 I53 NA NA NA NA NA NA NA NA 295
#> 54 I54 NA NA NA NA NA NA NA NA 0
#> 55 I55 0.1185 4.3102 -0.0157 -1.8017 21.4127 0.0000 0.0716 0.0000 505
#> 56 I56 NA NA NA NA NA NA NA NA 0
#> 57 I57 NA NA NA NA NA NA NA NA 24
#> 58 I58 0.1186 5.4560 -0.0058 -0.0980 35.7925 0.0000 0.9220 0.0000 669
#> 59 I59 NA NA NA NA NA NA NA NA 144
#> 60 I60 NA NA NA NA NA NA NA NA 131
#> 61 I61 0.0235 0.8622 0.0092 0.5312 1.8487 0.3886 0.5953 0.3968 554
#> 62 I62 0.0237 0.7408 -0.0011 0.1690 0.7826 0.4588 0.8658 0.6762 439
#> 63 I63 NA NA NA NA NA NA NA NA 139
#> 64 I64 0.0498 2.0571 -0.0001 -1.3609 4.2318 0.0397 0.1735 0.1205 634
#> 65 I65 NA NA NA NA NA NA NA NA 0
#> 66 I66 NA NA NA NA NA NA NA NA 403
#> 67 I67 NA NA NA NA NA NA NA NA 152
#> 68 I68 0.0181 0.5876 -0.0061 -1.4062 2.0857 0.5568 0.1597 0.3524 457
#> 69 I69 -0.0295 -0.8921 0.0030 -0.0464 1.4685 0.3723 0.9630 0.4799 406
#> 70 I70 NA NA NA NA NA NA NA NA 295
#> 71 I71 NA NA NA NA NA NA NA NA 2
#> 72 I72 NA NA NA NA NA NA NA NA 328
#> 73 I73 NA NA NA NA NA NA NA NA 0
#> 74 I74 0.0237 0.9350 -0.0004 -0.4478 0.8764 0.3498 0.6543 0.6452 619
#> 75 I75 -0.0264 -0.9324 0.0085 0.4927 0.8887 0.3511 0.6222 0.6412 528
#> 76 I76 NA NA NA NA NA NA NA NA 1
#> 77 I77 NA NA NA NA NA NA NA NA 0
#> 78 I78 NA NA NA NA NA NA NA NA 313
#> 79 I79 NA NA NA NA NA NA NA NA 271
#> 80 I80 NA NA NA NA NA NA NA NA 395
#> 81 I81 NA NA NA NA NA NA NA NA 389
#> 82 I82 NA NA NA NA NA NA NA NA 0
#> 83 I83 NA NA NA NA NA NA NA NA 317
#> 84 I84 -0.0068 -0.2119 -0.0101 -1.0513 2.1801 0.8322 0.2931 0.3362 443
#> 85 I85 NA NA NA NA NA NA NA NA 390
#> 86 I86 NA NA NA NA NA NA NA NA 0
#> 87 I87 NA NA NA NA NA NA NA NA 60
#> 88 I88 NA NA NA NA NA NA NA NA 265
#> 89 I89 NA NA NA NA NA NA NA NA 324
#> 90 I90 NA NA NA NA NA NA NA NA 374
#> 91 I91 NA NA NA NA NA NA NA NA 11
#> 92 I92 NA NA NA NA NA NA NA NA 57
#> 93 I93 NA NA NA NA NA NA NA NA 0
#> 94 I94 NA NA NA NA NA NA NA NA 1
#> 95 I95 NA NA NA NA NA NA NA NA 323
#> 96 I96 NA NA NA NA NA NA NA NA 90
#> 97 I97 0.1084 3.7826 -0.0060 -0.9349 16.6481 0.0002 0.3498 0.0002 520
#> 98 I98 NA NA NA NA NA NA NA NA 165
#> 99 I99 NA NA NA NA NA NA NA NA 250
#> 100 I100 NA NA NA NA NA NA NA NA 30
#> 101 I101 NA NA NA NA NA NA NA NA 28
#> 102 I102 NA NA NA NA NA NA NA NA 0
#> 103 I103 NA NA NA NA NA NA NA NA 265
#> 104 I104 NA NA NA NA NA NA NA NA 1
#> 105 I105 NA NA NA NA NA NA NA NA 0
#> 106 I106 NA NA NA NA NA NA NA NA 345
#> 107 I107 NA NA NA NA NA NA NA NA 169
#> 108 I108 NA NA NA NA NA NA NA NA 0
#> 109 I109 NA NA NA NA NA NA NA NA 344
#> 110 I110 NA NA NA NA NA NA NA NA 406
#> 111 I111 NA NA NA NA NA NA NA NA 0
#> 112 I112 NA NA NA NA NA NA NA NA 0
#> 113 I113 NA NA NA NA NA NA NA NA 1
#> 114 I114 NA NA NA NA NA NA NA NA 348
#> 115 I115 NA NA NA NA NA NA NA NA 349
#> 116 I116 NA NA NA NA NA NA NA NA 328
#> 117 I117 NA NA NA NA NA NA NA NA 139
#> 118 I118 NA NA NA NA NA NA NA NA 288
#> 119 I119 -0.0189 -0.6435 0.0061 0.8138 0.7097 0.5199 0.4158 0.7013 486
#> 120 I120 NA NA NA NA NA NA NA NA 0
#> 121 I121 NA NA NA NA NA NA NA NA 347
#> 122 I122 NA NA NA NA NA NA NA NA 0
#> 123 I123 NA NA NA NA NA NA NA NA 218
#> 124 I124 NA NA NA NA NA NA NA NA 7
#> 125 I125 NA NA NA NA NA NA NA NA 299
#> 126 I126 -0.0188 -0.6304 0.0051 0.3400 0.4122 0.5285 0.7339 0.8137 480
#> 127 I127 NA NA NA NA NA NA NA NA 2
#> 128 I128 NA NA NA NA NA NA NA NA 362
#> 129 I129 0.1368 5.3482 0.0103 0.8954 39.2596 0.0000 0.3706 0.0000 583
#> 130 I130 -0.0441 -1.4376 0.0373 2.1490 5.0819 0.1505 0.0316 0.0788 432
#> 131 I131 NA NA NA NA NA NA NA NA 0
#> 132 I132 NA NA NA NA NA NA NA NA 53
#> 133 I133 -0.0055 -0.2100 -0.0038 -0.6711 1.0608 0.8337 0.5022 0.5884 602
#> 134 I134 NA NA NA NA NA NA NA NA 168
#> 135 I135 NA NA NA NA NA NA NA NA 193
#> 136 I136 NA NA NA NA NA NA NA NA 21
#> 137 I137 NA NA NA NA NA NA NA NA 0
#> 138 I138 0.1398 5.5154 0.0161 1.9167 42.8797 0.0000 0.0553 0.0000 621
#> 139 I139 NA NA NA NA NA NA NA NA 302
#> 140 I140 NA NA NA NA NA NA NA NA 0
#> 141 I141 NA NA NA NA NA NA NA NA 139
#> 142 I142 NA NA NA NA NA NA NA NA 192
#> 143 I143 0.0482 1.5801 -0.0209 -1.8935 3.8420 0.1141 0.0583 0.1465 457
#> 144 I144 NA NA NA NA NA NA NA NA 0
#> 145 I145 0.1763 6.9759 -0.0147 -1.9648 60.2775 0.0000 0.0494 0.0000 615
#> 146 I146 -0.0077 -0.2988 0.0052 -0.2029 0.2941 0.7651 0.8392 0.8632 600
#> 147 I147 0.0373 1.1655 -0.0001 -0.3402 1.4920 0.2438 0.7337 0.4743 437
#> 148 I148 NA NA NA NA NA NA NA NA 274
#> 149 I149 0.1162 3.9102 -0.0103 -1.1677 16.3571 0.0001 0.2429 0.0003 496
#> 150 I150 NA NA NA NA NA NA NA NA 369
#> 151 I151 NA NA NA NA NA NA NA NA 214
#> 152 I152 -0.0312 -1.1832 0.0195 1.8089 4.1292 0.2367 0.0705 0.1269 583
#> 153 I153 0.0247 1.0828 -0.0047 -0.3052 1.1925 0.2789 0.7602 0.5509 713
#> 154 I154 NA NA NA NA NA NA NA NA 274
#> 155 I155 NA NA NA NA NA NA NA NA 0
#> 156 I156 NA NA NA NA NA NA NA NA 0
#> 157 I157 NA NA NA NA NA NA NA NA 98
#> 158 I158 NA NA NA NA NA NA NA NA 374
#> 159 I159 NA NA NA NA NA NA NA NA 108
#> 160 I160 NA NA NA NA NA NA NA NA 227
#> 161 I161 NA NA NA NA NA NA NA NA 431
#> 162 I162 0.0097 0.3857 0.0069 -1.0169 1.1785 0.6997 0.3092 0.5548 576
#> 163 I163 -0.0340 -1.3021 0.0019 0.1584 1.7251 0.1929 0.8741 0.4221 621
#> 164 I164 NA NA NA NA NA NA NA NA 0
#> 165 I165 NA NA NA NA NA NA NA NA 0
#> 166 I166 NA NA NA NA NA NA NA NA 127
#> 167 I167 0.0089 0.3280 -0.0026 0.1958 0.2126 0.7429 0.8448 0.8991 564
#> 168 I168 0.0490 1.6468 -0.0073 -1.2123 2.7469 0.0996 0.2254 0.2532 467
#> 169 I169 NA NA NA NA NA NA NA NA 415
#> 170 I170 NA NA NA NA NA NA NA NA 425
#> 171 I171 NA NA NA NA NA NA NA NA 299
#> 172 I172 NA NA NA NA NA NA NA NA 110
#> 173 I173 NA NA NA NA NA NA NA NA 439
#> 174 I174 NA NA NA NA NA NA NA NA 0
#> 175 I175 NA NA NA NA NA NA NA NA 434
#> 176 I176 NA NA NA NA NA NA NA NA 1
#> 177 I177 NA NA NA NA NA NA NA NA 373
#> 178 I178 NA NA NA NA NA NA NA NA 160
#> 179 I179 NA NA NA NA NA NA NA NA 414
#> 180 I180 NA NA NA NA NA NA NA NA 223
#> 181 I181 0.1107 4.8536 0.0009 -0.7843 26.6144 0.0000 0.4329 0.0000 666
#> 182 I182 NA NA NA NA NA NA NA NA 0
#> 183 I183 NA NA NA NA NA NA NA NA 375
#> 184 I184 0.1128 4.0685 -0.0167 -2.2657 16.5847 0.0000 0.0235 0.0003 546
#> 185 I185 NA NA NA NA NA NA NA NA 172
#> 186 I186 NA NA NA NA NA NA NA NA 383
#> 187 I187 0.0427 1.3015 -0.0115 -1.3289 2.1998 0.1931 0.1839 0.3329 414
#> 188 I188 -0.0036 -0.1509 0.0144 1.2625 1.7315 0.8801 0.2068 0.4207 692
#> 189 I189 NA NA NA NA NA NA NA NA 154
#> 190 I190 NA NA NA NA NA NA NA NA 121
#> 191 I191 NA NA NA NA NA NA NA NA 314
#> 192 I192 NA NA NA NA NA NA NA NA 23
#> 193 I193 NA NA NA NA NA NA NA NA 0
#> 194 I194 NA NA NA NA NA NA NA NA 184
#> 195 I195 NA NA NA NA NA NA NA NA 210
#> 196 I196 NA NA NA NA NA NA NA NA 0
#> 197 I197 NA NA NA NA NA NA NA NA 57
#> 198 I198 NA NA NA NA NA NA NA NA 19
#> 199 I199 -0.0159 -0.6478 0.0047 0.2427 0.4199 0.5171 0.8082 0.8106 634
#> 200 I200 NA NA NA NA NA NA NA NA 327
#> 201 I201 NA NA NA NA NA NA NA NA 0
#> 202 I202 -0.0188 -0.6575 -0.0019 -0.6402 1.3473 0.5109 0.5220 0.5098 529
#> 203 I203 0.0955 3.6313 -0.0099 -1.1256 24.1709 0.0003 0.2603 0.0000 549
#> 204 I204 NA NA NA NA NA NA NA NA 4
#> 205 I205 NA NA NA NA NA NA NA NA 3
#> 206 I206 NA NA NA NA NA NA NA NA 0
#> 207 I207 NA NA NA NA NA NA NA NA 3
#> 208 I208 NA NA NA NA NA NA NA NA 212
#> 209 I209 NA NA NA NA NA NA NA NA 288
#> 210 I210 0.0077 0.3441 0.0106 0.9224 1.1184 0.7308 0.3563 0.5717 711
#> 211 I211 NA NA NA NA NA NA NA NA 180
#> 212 I212 NA NA NA NA NA NA NA NA 1
#> 213 I213 NA NA NA NA NA NA NA NA 36
#> 214 I214 NA NA NA NA NA NA NA NA 3
#> 215 I215 -0.0488 -1.6031 0.0188 1.4784 3.3151 0.1089 0.1393 0.1906 474
#> 216 I216 NA NA NA NA NA NA NA NA 76
#> 217 I217 NA NA NA NA NA NA NA NA 274
#> 218 I218 0.0029 0.0922 -0.0020 -0.2043 0.0457 0.9265 0.8381 0.9774 424
#> 219 I219 NA NA NA NA NA NA NA NA 0
#> 220 I220 NA NA NA NA NA NA NA NA 12
#> 221 I221 NA NA NA NA NA NA NA NA 400
#> 222 I222 NA NA NA NA NA NA NA NA 0
#> 223 I223 NA NA NA NA NA NA NA NA 0
#> 224 I224 NA NA NA NA NA NA NA NA 157
#> 225 I225 NA NA NA NA NA NA NA NA 0
#> 226 I226 NA NA NA NA NA NA NA NA 161
#> 227 I227 0.0015 0.0612 0.0137 0.2031 0.0692 0.9512 0.8390 0.9660 613
#> 228 I228 NA NA NA NA NA NA NA NA 334
#> 229 I229 -0.0238 -0.7360 0.0065 0.6781 0.6392 0.4618 0.4977 0.7264 440
#> 230 I230 NA NA NA NA NA NA NA NA 123
#> 231 I231 -0.0408 -1.5595 0.0215 1.1681 2.4786 0.1189 0.2428 0.2896 575
#> 232 I232 NA NA NA NA NA NA NA NA 0
#> 233 I233 NA NA NA NA NA NA NA NA 49
#> 234 I234 NA NA NA NA NA NA NA NA 106
#> 235 I235 -0.0079 -0.2740 0.0031 -0.1643 0.2253 0.7841 0.8695 0.8935 509
#> 236 I236 0.0271 1.0830 0.0186 1.5431 9.1061 0.2788 0.1228 0.0105 638
#> 237 I237 0.0025 0.0883 -0.0080 -1.1335 1.4236 0.9297 0.2570 0.4908 550
#> 238 I238 NA NA NA NA NA NA NA NA 360
#> 239 I239 NA NA NA NA NA NA NA NA 357
#> 240 I240 NA NA NA NA NA NA NA NA 326
#> 241 I241 NA NA NA NA NA NA NA NA 0
#> 242 I242 0.1273 4.1197 -0.0038 -0.9586 19.8205 0.0000 0.3378 0.0000 477
#> 243 I243 NA NA NA NA NA NA NA NA 221
#> 244 I244 -0.0163 -0.6155 0.0214 1.2056 1.4951 0.5382 0.2280 0.4735 562
#> 245 I245 NA NA NA NA NA NA NA NA 244
#> 246 I246 0.1343 5.8707 0.0009 0.2762 46.2651 0.0000 0.7824 0.0000 692
#> 247 I247 NA NA NA NA NA NA NA NA 70
#> 248 I248 0.0220 0.7574 0.0075 -0.6135 0.5738 0.4488 0.5396 0.7506 457
#> 249 I249 0.0214 0.7433 0.0020 -0.0650 0.5690 0.4573 0.9482 0.7524 486
#> 250 I250 -0.0096 -0.3642 0.0017 -0.0513 0.2441 0.7157 0.9591 0.8851 555
#> 251 I251 NA NA NA NA NA NA NA NA 362
#> 252 I252 0.1056 4.5764 -0.0022 -0.3684 25.5749 0.0000 0.7126 0.0000 644
#> 253 I253 0.0056 0.1833 -0.0071 -0.5397 0.2915 0.8545 0.5894 0.8644 480
#> 254 I254 NA NA NA NA NA NA NA NA 363
#> 255 I255 NA NA NA NA NA NA NA NA 0
#> 256 I256 NA NA NA NA NA NA NA NA 377
#> 257 I257 NA NA NA NA NA NA NA NA 187
#> 258 I258 NA NA NA NA NA NA NA NA 442
#> 259 I259 NA NA NA NA NA NA NA NA 242
#> 260 I260 NA NA NA NA NA NA NA NA 71
#> 261 I261 0.0428 1.5036 -0.0074 -1.3818 2.3219 0.1327 0.1670 0.3132 493
#> 262 I262 NA NA NA NA NA NA NA NA 96
#> 263 I263 NA NA NA NA NA NA NA NA 168
#> 264 I264 NA NA NA NA NA NA NA NA 175
#> 265 I265 NA NA NA NA NA NA NA NA 0
#> 266 I266 NA NA NA NA NA NA NA NA 226
#> 267 I267 NA NA NA NA NA NA NA NA 128
#> 268 I268 NA NA NA NA NA NA NA NA 376
#> 269 I269 NA NA NA NA NA NA NA NA 0
#> 270 I270 0.0423 1.3948 -0.0031 -0.3813 3.2837 0.1631 0.7030 0.1936 434
#> 271 I271 NA NA NA NA NA NA NA NA 0
#> 272 I272 0.0150 0.5582 -0.0050 -0.7055 0.5174 0.5767 0.4805 0.7721 565
#> 273 I273 NA NA NA NA NA NA NA NA 362
#> 274 I274 NA NA NA NA NA NA NA NA 14
#> 275 I275 NA NA NA NA NA NA NA NA 21
#> 276 I276 0.0032 0.1140 -0.0052 -1.1289 1.8557 0.9092 0.2590 0.3954 548
#> 277 I277 -0.0573 -1.8253 0.0195 1.1559 3.3487 0.0680 0.2477 0.1874 442
#> 278 I278 NA NA NA NA NA NA NA NA 0
#> 279 I279 NA NA NA NA NA NA NA NA 0
#> 280 I280 NA NA NA NA NA NA NA NA 296
#> 281 I281 NA NA NA NA NA NA NA NA 211
#> 282 I282 NA NA NA NA NA NA NA NA 373
#> 283 I283 NA NA NA NA NA NA NA NA 252
#> 284 I284 NA NA NA NA NA NA NA NA 0
#> 285 I285 NA NA NA NA NA NA NA NA 187
#> 286 I286 NA NA NA NA NA NA NA NA 0
#> 287 I287 NA NA NA NA NA NA NA NA 6
#> 288 I288 NA NA NA NA NA NA NA NA 337
#> 289 I289 NA NA NA NA NA NA NA NA 0
#> 290 I290 NA NA NA NA NA NA NA NA 260
#> 291 I291 NA NA NA NA NA NA NA NA 0
#> 292 I292 NA NA NA NA NA NA NA NA 0
#> 293 I293 NA NA NA NA NA NA NA NA 0
#> 294 I294 NA NA NA NA NA NA NA NA 339
#> 295 I295 NA NA NA NA NA NA NA NA 0
#> 296 I296 -0.0255 -1.0457 0.0033 -0.5004 1.5984 0.2957 0.6168 0.4497 636
#> 297 I297 NA NA NA NA NA NA NA NA 121
#> 298 I298 -0.0205 -0.8848 0.0104 0.8084 1.1706 0.3762 0.4189 0.5569 713
#> 299 I299 NA NA NA NA NA NA NA NA 188
#> 300 I300 -0.0086 -0.3233 0.0014 -0.1464 0.1832 0.7465 0.8836 0.9124 586
#> 301 I301 NA NA NA NA NA NA NA NA 327
#> 302 I302 NA NA NA NA NA NA NA NA 395
#> 303 I303 NA NA NA NA NA NA NA NA 188
#> 304 I304 NA NA NA NA NA NA NA NA 311
#> 305 I305 NA NA NA NA NA NA NA NA 0
#> 306 I306 -0.0266 -0.9104 0.0028 -0.9889 2.8219 0.3626 0.3227 0.2439 439
#> 307 I307 NA NA NA NA NA NA NA NA 1
#> 308 I308 NA NA NA NA NA NA NA NA 110
#> 309 I309 NA NA NA NA NA NA NA NA 140
#> 310 I310 0.1143 4.1297 -0.0146 -1.5722 19.1547 0.0000 0.1159 0.0001 523
#> 311 I311 -0.0219 -0.6930 0.0033 -0.3245 1.5462 0.4883 0.7456 0.4616 432
#> 312 I312 -0.0442 -1.6179 0.0093 -0.1372 3.4609 0.1057 0.8909 0.1772 506
#> 313 I313 NA NA NA NA NA NA NA NA 0
#> 314 I314 NA NA NA NA NA NA NA NA 301
#> 315 I315 NA NA NA NA NA NA NA NA 0
#> 316 I316 NA NA NA NA NA NA NA NA 0
#> 317 I317 NA NA NA NA NA NA NA NA 63
#> 318 I318 NA NA NA NA NA NA NA NA 340
#> 319 I319 NA NA NA NA NA NA NA NA 369
#> 320 I320 NA NA NA NA NA NA NA NA 349
#> 321 I321 NA NA NA NA NA NA NA NA 38
#> 322 I322 0.0030 0.1215 0.0131 0.7260 0.8537 0.9033 0.4679 0.6526 626
#> 323 I323 NA NA NA NA NA NA NA NA 218
#> 324 I324 NA NA NA NA NA NA NA NA 418
#> 325 I325 0.0037 0.1464 0.0017 -0.3384 0.1175 0.8836 0.7351 0.9429 627
#> 326 I326 NA NA NA NA NA NA NA NA 252
#> 327 I327 -0.0217 -0.7565 0.0092 0.2144 0.7619 0.4493 0.8303 0.6832 506
#> 328 I328 NA NA NA NA NA NA NA NA 374
#> 329 I329 NA NA NA NA NA NA NA NA 124
#> 330 I330 NA NA NA NA NA NA NA NA 177
#> 331 I331 -0.0006 -0.0192 0.0027 -0.1772 0.0431 0.9847 0.8594 0.9787 504
#> 332 I332 NA NA NA NA NA NA NA NA 326
#> 333 I333 NA NA NA NA NA NA NA NA 127
#> 334 I334 0.1759 7.1779 -0.0083 -0.9826 59.8699 0.0000 0.3258 0.0000 659
#> 335 I335 NA NA NA NA NA NA NA NA 89
#> 336 I336 0.1218 4.1671 0.0024 0.1119 19.9905 0.0000 0.9109 0.0000 520
#> 337 I337 -0.0333 -1.3067 0.0020 -0.0568 2.7847 0.1913 0.9547 0.2485 596
#> 338 I338 NA NA NA NA NA NA NA NA 350
#> 339 I339 NA NA NA NA NA NA NA NA 0
#> 340 I340 NA NA NA NA NA NA NA NA 239
#> 341 I341 NA NA NA NA NA NA NA NA 316
#> 342 I342 NA NA NA NA NA NA NA NA 0
#> 343 I343 NA NA NA NA NA NA NA NA 0
#> 344 I344 NA NA NA NA NA NA NA NA 0
#> 345 I345 NA NA NA NA NA NA NA NA 0
#> 346 I346 NA NA NA NA NA NA NA NA 167
#> 347 I347 0.0143 0.5557 -0.0077 -1.2092 1.4877 0.5784 0.2266 0.4753 610
#> 348 I348 NA NA NA NA NA NA NA NA 429
#> 349 I349 NA NA NA NA NA NA NA NA 67
#> 350 I350 NA NA NA NA NA NA NA NA 151
#> 351 I351 -0.0562 -2.0962 0.0082 0.8773 4.5062 0.0361 0.3803 0.1051 549
#> 352 I352 NA NA NA NA NA NA NA NA 0
#> 353 I353 NA NA NA NA NA NA NA NA 0
#> 354 I354 -0.0228 -0.7703 -0.0134 -1.1739 5.4862 0.4411 0.2404 0.0644 474
#> 355 I355 NA NA NA NA NA NA NA NA 298
#> 356 I356 NA NA NA NA NA NA NA NA 273
#> 357 I357 NA NA NA NA NA NA NA NA 77
#> 358 I358 -0.0128 -0.5044 0.0140 2.1553 4.8701 0.6140 0.0311 0.0876 634
#> 359 I359 NA NA NA NA NA NA NA NA 0
#> 360 I360 NA NA NA NA NA NA NA NA 213
#> n.foc n.total n.iter
#> 1 4 6 20
#> 2 433 862 20
#> 3 700 1398 20
#> 4 235 456 20
#> 5 73 158 20
#> 6 56 117 20
#> 7 108 212 20
#> 8 184 363 20
#> 9 14 33 20
#> 10 516 1026 20
#> 11 158 334 20
#> 12 1 1 20
#> 13 598 1194 19
#> 14 453 895 20
#> 15 482 954 20
#> 16 17 38 20
#> 17 0 0 20
#> 18 665 1329 20
#> 19 0 0 20
#> 20 492 1012 20
#> 21 127 241 20
#> 22 0 0 20
#> 23 552 1135 20
#> 24 0 0 20
#> 25 506 1012 20
#> 26 521 1036 13
#> 27 0 0 20
#> 28 87 170 20
#> 29 19 46 20
#> 30 0 0 20
#> 31 678 1350 20
#> 32 0 0 20
#> 33 356 707 20
#> 34 0 0 20
#> 35 657 1313 20
#> 36 65 132 20
#> 37 69 138 20
#> 38 129 265 20
#> 39 136 281 20
#> 40 99 206 20
#> 41 61 130 20
#> 42 479 953 17
#> 43 510 1018 20
#> 44 0 0 20
#> 45 74 137 20
#> 46 172 358 20
#> 47 0 0 20
#> 48 386 768 20
#> 49 208 427 20
#> 50 0 0 20
#> 51 318 639 20
#> 52 327 651 20
#> 53 296 591 20
#> 54 0 0 20
#> 55 512 1017 9
#> 56 0 0 20
#> 57 21 45 20
#> 58 665 1334 4
#> 59 137 281 20
#> 60 121 252 20
#> 61 557 1111 20
#> 62 441 880 20
#> 63 123 262 20
#> 64 640 1274 20
#> 65 0 0 20
#> 66 404 807 20
#> 67 156 308 20
#> 68 460 917 20
#> 69 398 804 20
#> 70 276 571 20
#> 71 1 3 20
#> 72 329 657 20
#> 73 0 0 20
#> 74 621 1240 20
#> 75 536 1064 20
#> 76 0 1 20
#> 77 0 0 20
#> 78 311 624 20
#> 79 278 549 20
#> 80 407 802 20
#> 81 392 781 20
#> 82 0 0 20
#> 83 300 617 20
#> 84 443 886 20
#> 85 394 784 20
#> 86 0 0 20
#> 87 52 112 20
#> 88 271 536 20
#> 89 307 631 20
#> 90 384 758 20
#> 91 7 18 20
#> 92 56 113 20
#> 93 0 0 20
#> 94 3 4 20
#> 95 329 652 20
#> 96 93 183 20
#> 97 529 1049 16
#> 98 138 303 20
#> 99 250 500 20
#> 100 35 65 20
#> 101 23 51 20
#> 102 0 0 20
#> 103 252 517 20
#> 104 1 2 20
#> 105 0 0 20
#> 106 350 695 20
#> 107 182 351 20
#> 108 0 0 20
#> 109 354 698 20
#> 110 406 812 20
#> 111 0 0 20
#> 112 0 0 20
#> 113 1 2 20
#> 114 354 702 20
#> 115 338 687 20
#> 116 313 641 20
#> 117 142 281 20
#> 118 288 576 20
#> 119 491 977 20
#> 120 0 0 20
#> 121 352 699 20
#> 122 0 0 20
#> 123 207 425 20
#> 124 13 20 20
#> 125 302 601 20
#> 126 483 963 20
#> 127 2 4 20
#> 128 369 731 20
#> 129 577 1160 5
#> 130 410 842 20
#> 131 0 0 20
#> 132 42 95 20
#> 133 603 1205 20
#> 134 174 342 20
#> 135 184 377 20
#> 136 14 35 20
#> 137 0 0 20
#> 138 624 1245 3
#> 139 289 591 20
#> 140 0 0 20
#> 141 148 287 20
#> 142 201 393 20
#> 143 464 921 20
#> 144 0 0 20
#> 145 622 1237 1
#> 146 598 1198 20
#> 147 447 884 20
#> 148 268 542 20
#> 149 503 999 14
#> 150 367 736 20
#> 151 221 435 20
#> 152 588 1171 20
#> 153 716 1429 20
#> 154 281 555 20
#> 155 0 0 20
#> 156 0 0 20
#> 157 88 186 20
#> 158 379 753 20
#> 159 111 219 20
#> 160 234 461 20
#> 161 442 873 20
#> 162 582 1158 20
#> 163 622 1243 20
#> 164 0 0 20
#> 165 0 0 20
#> 166 136 263 20
#> 167 568 1132 20
#> 168 478 945 20
#> 169 413 828 20
#> 170 429 854 20
#> 171 278 577 20
#> 172 118 228 20
#> 173 445 884 20
#> 174 0 0 20
#> 175 435 869 20
#> 176 0 1 20
#> 177 348 721 20
#> 178 173 333 20
#> 179 421 835 20
#> 180 212 435 20
#> 181 670 1336 7
#> 182 0 0 20
#> 183 356 731 20
#> 184 554 1100 15
#> 185 172 344 20
#> 186 385 768 20
#> 187 420 834 20
#> 188 695 1387 20
#> 189 168 322 20
#> 190 119 240 20
#> 191 313 627 20
#> 192 30 53 20
#> 193 0 0 20
#> 194 199 383 20
#> 195 211 421 20
#> 196 0 0 20
#> 197 54 111 20
#> 198 25 44 20
#> 199 637 1271 20
#> 200 322 649 20
#> 201 0 0 20
#> 202 533 1062 20
#> 203 558 1107 8
#> 204 2 6 20
#> 205 2 5 20
#> 206 0 0 20
#> 207 1 4 20
#> 208 216 428 20
#> 209 263 551 20
#> 210 713 1424 20
#> 211 188 368 20
#> 212 1 2 20
#> 213 41 77 20
#> 214 3 6 20
#> 215 477 951 20
#> 216 69 145 20
#> 217 258 532 20
#> 218 427 851 20
#> 219 0 0 20
#> 220 8 20 20
#> 221 397 797 20
#> 222 0 0 20
#> 223 0 0 20
#> 224 173 330 20
#> 225 0 0 20
#> 226 151 312 20
#> 227 618 1231 20
#> 228 347 681 20
#> 229 445 885 20
#> 230 128 251 20
#> 231 583 1158 20
#> 232 0 0 20
#> 233 40 89 20
#> 234 96 202 20
#> 235 511 1020 20
#> 236 639 1277 18
#> 237 556 1106 20
#> 238 366 726 20
#> 239 356 713 20
#> 240 315 641 20
#> 241 0 0 20
#> 242 487 964 11
#> 243 204 425 20
#> 244 564 1126 20
#> 245 245 489 20
#> 246 693 1385 2
#> 247 63 133 20
#> 248 459 916 20
#> 249 492 978 20
#> 250 560 1115 20
#> 251 368 730 20
#> 252 645 1289 6
#> 253 486 966 20
#> 254 369 732 20
#> 255 0 0 20
#> 256 385 762 20
#> 257 176 363 20
#> 258 449 891 20
#> 259 235 477 20
#> 260 61 132 20
#> 261 498 991 20
#> 262 88 184 20
#> 263 168 336 20
#> 264 179 354 20
#> 265 0 0 20
#> 266 221 447 20
#> 267 135 263 20
#> 268 389 765 20
#> 269 0 0 20
#> 270 439 873 20
#> 271 0 0 20
#> 272 567 1132 20
#> 273 368 730 20
#> 274 21 35 20
#> 275 16 37 20
#> 276 549 1097 20
#> 277 451 893 20
#> 278 0 0 20
#> 279 0 0 20
#> 280 282 578 20
#> 281 197 408 20
#> 282 376 749 20
#> 283 256 508 20
#> 284 0 0 20
#> 285 199 386 20
#> 286 0 0 20
#> 287 5 11 20
#> 288 342 679 20
#> 289 0 0 20
#> 290 263 523 20
#> 291 0 0 20
#> 292 0 0 20
#> 293 0 0 20
#> 294 344 683 20
#> 295 0 0 20
#> 296 640 1276 20
#> 297 135 256 20
#> 298 715 1428 20
#> 299 189 377 20
#> 300 589 1175 20
#> 301 334 661 20
#> 302 406 801 20
#> 303 188 376 20
#> 304 324 635 20
#> 305 0 0 20
#> 306 408 847 20
#> 307 2 3 20
#> 308 106 216 20
#> 309 134 274 20
#> 310 526 1049 12
#> 311 426 858 20
#> 312 476 982 20
#> 313 0 0 20
#> 314 302 603 20
#> 315 0 0 20
#> 316 0 0 20
#> 317 52 115 20
#> 318 320 660 20
#> 319 371 740 20
#> 320 336 685 20
#> 321 30 68 20
#> 322 630 1256 20
#> 323 206 424 20
#> 324 430 848 20
#> 325 626 1253 20
#> 326 252 504 20
#> 327 516 1022 20
#> 328 378 752 20
#> 329 117 241 20
#> 330 166 343 20
#> 331 507 1011 20
#> 332 332 658 20
#> 333 110 237 20
#> 334 658 1317 0
#> 335 96 185 20
#> 336 526 1046 10
#> 337 601 1197 20
#> 338 326 676 20
#> 339 0 0 20
#> 340 242 481 20
#> 341 330 646 20
#> 342 0 0 20
#> 343 0 0 20
#> 344 0 0 20
#> 345 0 0 20
#> 346 153 320 20
#> 347 617 1227 20
#> 348 440 869 20
#> 349 60 127 20
#> 350 155 306 20
#> 351 553 1102 20
#> 352 0 0 20
#> 353 0 0 20
#> 354 479 953 20
#> 355 306 604 20
#> 356 273 546 20
#> 357 72 149 20
#> 358 637 1271 20
#> 359 0 0 20
#> 360 218 431 20
#>
#> $with_purify$moments
#> id mu.ripdr sigma.ripdr mu.ripds sigma.ripds covariance n.iter
#> 1 I1 NA NA NA NA NA 20
#> 2 I2 0 0.03198329 0.0032459482 0.009588278 -1.898330e-04 20
#> 3 I3 0 0.02338277 0.0004757258 0.008977362 -3.910212e-05 20
#> 4 I4 NA NA NA NA NA 20
#> 5 I5 NA NA NA NA NA 20
#> 6 I6 NA NA NA NA NA 20
#> 7 I7 NA NA NA NA NA 20
#> 8 I8 NA NA NA NA NA 20
#> 9 I9 NA NA NA NA NA 20
#> 10 I10 0 0.02906672 -0.0013147666 0.009319493 -1.107036e-04 20
#> 11 I11 NA NA NA NA NA 20
#> 12 I12 NA NA NA NA NA 20
#> 13 I13 0 0.02499273 0.0111740254 0.010067087 -1.709532e-04 19
#> 14 I14 0 0.03121368 0.0085444876 0.010134252 -2.336570e-04 20
#> 15 I15 0 0.03042803 0.0049068764 0.009398134 -1.885606e-04 20
#> 16 I16 NA NA NA NA NA 20
#> 17 I17 NA NA NA NA NA 20
#> 18 I18 0 0.02453821 0.0014905630 0.008667375 -6.134836e-05 20
#> 19 I19 NA NA NA NA NA 20
#> 20 I20 0 0.02599236 0.0116950773 0.011751932 -1.873654e-04 20
#> 21 I21 NA NA NA NA NA 20
#> 22 I22 NA NA NA NA NA 20
#> 23 I23 0 0.02344813 0.0120427332 0.011525396 -8.976648e-05 20
#> 24 I24 NA NA NA NA NA 20
#> 25 I25 0 0.02901890 0.0062966143 0.008991598 -8.974673e-05 20
#> 26 I26 0 0.02723484 0.0073651252 0.011207461 -2.355673e-04 13
#> 27 I27 NA NA NA NA NA 20
#> 28 I28 NA NA NA NA NA 20
#> 29 I29 NA NA NA NA NA 20
#> 30 I30 NA NA NA NA NA 20
#> 31 I31 0 0.02422587 0.0041490873 0.008747155 -7.611161e-05 20
#> 32 I32 NA NA NA NA NA 20
#> 33 I33 NA NA NA NA NA 20
#> 34 I34 NA NA NA NA NA 20
#> 35 I35 0 0.02477275 -0.0038346768 0.008729960 -7.096998e-05 20
#> 36 I36 NA NA NA NA NA 20
#> 37 I37 NA NA NA NA NA 20
#> 38 I38 NA NA NA NA NA 20
#> 39 I39 NA NA NA NA NA 20
#> 40 I40 NA NA NA NA NA 20
#> 41 I41 NA NA NA NA NA 20
#> 42 I42 0 0.03014815 0.0094838766 0.009526871 -1.892318e-04 17
#> 43 I43 0 0.02816905 0.0024907633 0.010607884 -2.033860e-04 20
#> 44 I44 NA NA NA NA NA 20
#> 45 I45 NA NA NA NA NA 20
#> 46 I46 NA NA NA NA NA 20
#> 47 I47 NA NA NA NA NA 20
#> 48 I48 NA NA NA NA NA 20
#> 49 I49 NA NA NA NA NA 20
#> 50 I50 NA NA NA NA NA 20
#> 51 I51 NA NA NA NA NA 20
#> 52 I52 NA NA NA NA NA 20
#> 53 I53 NA NA NA NA NA 20
#> 54 I54 NA NA NA NA NA 20
#> 55 I55 0 0.02750387 0.0038173287 0.010815609 -2.075802e-04 9
#> 56 I56 NA NA NA NA NA 20
#> 57 I57 NA NA NA NA NA 20
#> 58 I58 0 0.02173577 -0.0048018440 0.009939476 -9.184967e-05 4
#> 59 I59 NA NA NA NA NA 20
#> 60 I60 NA NA NA NA NA 20
#> 61 I61 0 0.02731175 0.0043093189 0.009193950 -1.165116e-04 20
#> 62 I62 0 0.03201270 -0.0025592806 0.008683992 -1.046934e-04 20
#> 63 I63 NA NA NA NA NA 20
#> 64 I64 0 0.02421120 0.0133829950 0.009914471 -1.599090e-04 20
#> 65 I65 NA NA NA NA NA 20
#> 66 I66 NA NA NA NA NA 20
#> 67 I67 NA NA NA NA NA 20
#> 68 I68 0 0.03081140 0.0071635719 0.009426208 -1.754885e-04 20
#> 69 I69 0 0.03301862 0.0034492752 0.010423571 -2.230660e-04 20
#> 70 I70 NA NA NA NA NA 20
#> 71 I71 NA NA NA NA NA 20
#> 72 I72 NA NA NA NA NA 20
#> 73 I73 NA NA NA NA NA 20
#> 74 I74 0 0.02531410 0.0037655707 0.009218173 -1.015586e-04 20
#> 75 I75 0 0.02830189 0.0038915786 0.009449371 -1.718935e-04 20
#> 76 I76 NA NA NA NA NA 20
#> 77 I77 NA NA NA NA NA 20
#> 78 I78 NA NA NA NA NA 20
#> 79 I79 NA NA NA NA NA 20
#> 80 I80 NA NA NA NA NA 20
#> 81 I81 NA NA NA NA NA 20
#> 82 I82 NA NA NA NA NA 20
#> 83 I83 NA NA NA NA NA 20
#> 84 I84 0 0.03193038 -0.0008210129 0.008823979 -1.669987e-04 20
#> 85 I85 NA NA NA NA NA 20
#> 86 I86 NA NA NA NA NA 20
#> 87 I87 NA NA NA NA NA 20
#> 88 I88 NA NA NA NA NA 20
#> 89 I89 NA NA NA NA NA 20
#> 90 I90 NA NA NA NA NA 20
#> 91 I91 NA NA NA NA NA 20
#> 92 I92 NA NA NA NA NA 20
#> 93 I93 NA NA NA NA NA 20
#> 94 I94 NA NA NA NA NA 20
#> 95 I95 NA NA NA NA NA 20
#> 96 I96 NA NA NA NA NA 20
#> 97 I97 0 0.02866324 0.0024986088 0.009059581 -1.499204e-04 16
#> 98 I98 NA NA NA NA NA 20
#> 99 I99 NA NA NA NA NA 20
#> 100 I100 NA NA NA NA NA 20
#> 101 I101 NA NA NA NA NA 20
#> 102 I102 NA NA NA NA NA 20
#> 103 I103 NA NA NA NA NA 20
#> 104 I104 NA NA NA NA NA 20
#> 105 I105 NA NA NA NA NA 20
#> 106 I106 NA NA NA NA NA 20
#> 107 I107 NA NA NA NA NA 20
#> 108 I108 NA NA NA NA NA 20
#> 109 I109 NA NA NA NA NA 20
#> 110 I110 NA NA NA NA NA 20
#> 111 I111 NA NA NA NA NA 20
#> 112 I112 NA NA NA NA NA 20
#> 113 I113 NA NA NA NA NA 20
#> 114 I114 NA NA NA NA NA 20
#> 115 I115 NA NA NA NA NA 20
#> 116 I116 NA NA NA NA NA 20
#> 117 I117 NA NA NA NA NA 20
#> 118 I118 NA NA NA NA NA 20
#> 119 I119 0 0.02942149 -0.0020369131 0.010000495 -1.679498e-04 20
#> 120 I120 NA NA NA NA NA 20
#> 121 I121 NA NA NA NA NA 20
#> 122 I122 NA NA NA NA NA 20
#> 123 I123 NA NA NA NA NA 20
#> 124 I124 NA NA NA NA NA 20
#> 125 I125 NA NA NA NA NA 20
#> 126 I126 0 0.02986016 0.0016933477 0.009897137 -2.012323e-04 20
#> 127 I127 NA NA NA NA NA 20
#> 128 I128 NA NA NA NA NA 20
#> 129 I129 0 0.02557285 0.0013393554 0.010013540 -1.008074e-04 5
#> 130 I130 0 0.03070716 0.0104109219 0.012504142 -1.440659e-04 20
#> 131 I131 NA NA NA NA NA 20
#> 132 I132 NA NA NA NA NA 20
#> 133 I133 0 0.02624943 0.0023074243 0.009135727 -1.462495e-04 20
#> 134 I134 NA NA NA NA NA 20
#> 135 I135 NA NA NA NA NA 20
#> 136 I136 NA NA NA NA NA 20
#> 137 I137 NA NA NA NA NA 20
#> 138 I138 0 0.02534998 -0.0013752182 0.009094123 -6.199598e-05 3
#> 139 I139 NA NA NA NA NA 20
#> 140 I140 NA NA NA NA NA 20
#> 141 I141 NA NA NA NA NA 20
#> 142 I142 NA NA NA NA NA 20
#> 143 I143 0 0.03050657 -0.0018746017 0.010055286 -1.919609e-04 20
#> 144 I144 NA NA NA NA NA 20
#> 145 I145 0 0.02527366 0.0041401941 0.009568876 -1.576918e-04 1
#> 146 I146 0 0.02588583 0.0071247645 0.009392643 -1.380746e-04 20
#> 147 I147 0 0.03201434 0.0027816893 0.008563507 -1.516746e-04 20
#> 148 I148 NA NA NA NA NA 20
#> 149 I149 0 0.02972926 -0.0002378551 0.008589680 -1.337354e-04 14
#> 150 I150 NA NA NA NA NA 20
#> 151 I151 NA NA NA NA NA 20
#> 152 I152 0 0.02640563 0.0024685800 0.009438633 -3.687643e-05 20
#> 153 I153 0 0.02278341 -0.0019720433 0.009061670 -3.152508e-05 20
#> 154 I154 NA NA NA NA NA 20
#> 155 I155 NA NA NA NA NA 20
#> 156 I156 NA NA NA NA NA 20
#> 157 I157 NA NA NA NA NA 20
#> 158 I158 NA NA NA NA NA 20
#> 159 I159 NA NA NA NA NA 20
#> 160 I160 NA NA NA NA NA 20
#> 161 I161 NA NA NA NA NA 20
#> 162 I162 0 0.02523923 0.0173281265 0.010303129 -1.716101e-04 20
#> 163 I163 0 0.02609694 0.0005552354 0.008328094 -5.423771e-05 20
#> 164 I164 NA NA NA NA NA 20
#> 165 I165 NA NA NA NA NA 20
#> 166 I166 NA NA NA NA NA 20
#> 167 I167 0 0.02712938 -0.0044840446 0.009423509 -8.545999e-05 20
#> 168 I168 0 0.02978429 0.0058560066 0.010856771 -2.599035e-04 20
#> 169 I169 NA NA NA NA NA 20
#> 170 I170 NA NA NA NA NA 20
#> 171 I171 NA NA NA NA NA 20
#> 172 I172 NA NA NA NA NA 20
#> 173 I173 NA NA NA NA NA 20
#> 174 I174 NA NA NA NA NA 20
#> 175 I175 NA NA NA NA NA 20
#> 176 I176 NA NA NA NA NA 20
#> 177 I177 NA NA NA NA NA 20
#> 178 I178 NA NA NA NA NA 20
#> 179 I179 NA NA NA NA NA 20
#> 180 I180 NA NA NA NA NA 20
#> 181 I181 0 0.02281096 0.0083409253 0.009540122 -1.040231e-04 7
#> 182 I182 NA NA NA NA NA 20
#> 183 I183 NA NA NA NA NA 20
#> 184 I184 0 0.02773637 0.0045425494 0.009365065 -1.538783e-04 15
#> 185 I185 NA NA NA NA NA 20
#> 186 I186 NA NA NA NA NA 20
#> 187 I187 0 0.03282318 0.0008512724 0.009284250 -1.747161e-04 20
#> 188 I188 0 0.02377036 0.0031081621 0.008905513 -8.257903e-05 20
#> 189 I189 NA NA NA NA NA 20
#> 190 I190 NA NA NA NA NA 20
#> 191 I191 NA NA NA NA NA 20
#> 192 I192 NA NA NA NA NA 20
#> 193 I193 NA NA NA NA NA 20
#> 194 I194 NA NA NA NA NA 20
#> 195 I195 NA NA NA NA NA 20
#> 196 I196 NA NA NA NA NA 20
#> 197 I197 NA NA NA NA NA 20
#> 198 I198 NA NA NA NA NA 20
#> 199 I199 0 0.02458744 0.0023042530 0.009871291 -8.559141e-05 20
#> 200 I200 NA NA NA NA NA 20
#> 201 I201 NA NA NA NA NA 20
#> 202 I202 0 0.02864175 0.0036200944 0.008577106 -9.212558e-05 20
#> 203 I203 0 0.02630299 0.0026235421 0.011162962 -2.423328e-04 8
#> 204 I204 NA NA NA NA NA 20
#> 205 I205 NA NA NA NA NA 20
#> 206 I206 NA NA NA NA NA 20
#> 207 I207 NA NA NA NA NA 20
#> 208 I208 NA NA NA NA NA 20
#> 209 I209 NA NA NA NA NA 20
#> 210 I210 0 0.02246679 0.0018067678 0.009530868 -3.826812e-05 20
#> 211 I211 NA NA NA NA NA 20
#> 212 I212 NA NA NA NA NA 20
#> 213 I213 NA NA NA NA NA 20
#> 214 I214 NA NA NA NA NA 20
#> 215 I215 0 0.03042088 0.0053706629 0.009061724 -1.208090e-04 20
#> 216 I216 NA NA NA NA NA 20
#> 217 I217 NA NA NA NA NA 20
#> 218 I218 0 0.03196477 0.0001064052 0.010125672 -2.190661e-04 20
#> 219 I219 NA NA NA NA NA 20
#> 220 I220 NA NA NA NA NA 20
#> 221 I221 NA NA NA NA NA 20
#> 222 I222 NA NA NA NA NA 20
#> 223 I223 NA NA NA NA NA 20
#> 224 I224 NA NA NA NA NA 20
#> 225 I225 NA NA NA NA NA 20
#> 226 I226 NA NA NA NA NA 20
#> 227 I227 0 0.02506553 0.0117587477 0.009407345 -1.034707e-04 20
#> 228 I228 NA NA NA NA NA 20
#> 229 I229 0 0.03230647 0.0010877835 0.008050674 -1.492456e-04 20
#> 230 I230 NA NA NA NA NA 20
#> 231 I231 0 0.02617810 0.0100028200 0.009850563 -1.657961e-04 20
#> 232 I232 NA NA NA NA NA 20
#> 233 I233 NA NA NA NA NA 20
#> 234 I234 NA NA NA NA NA 20
#> 235 I235 0 0.02876449 0.0046979359 0.009531270 -1.552627e-04 20
#> 236 I236 0 0.02501926 0.0040993833 0.009405929 -1.455708e-04 18
#> 237 I237 0 0.02831629 0.0011032075 0.008037561 -8.686679e-05 20
#> 238 I238 NA NA NA NA NA 20
#> 239 I239 NA NA NA NA NA 20
#> 240 I240 NA NA NA NA NA 20
#> 241 I241 NA NA NA NA NA 20
#> 242 I242 0 0.03089236 0.0035120926 0.007634699 -1.343142e-04 11
#> 243 I243 NA NA NA NA NA 20
#> 244 I244 0 0.02640863 0.0093755374 0.009978481 -1.687992e-04 20
#> 245 I245 NA NA NA NA NA 20
#> 246 I246 0 0.02287797 -0.0016491668 0.009186661 -9.868910e-05 2
#> 247 I247 NA NA NA NA NA 20
#> 248 I248 0 0.02899759 0.0146669709 0.011625427 -2.694935e-04 20
#> 249 I249 0 0.02876403 0.0026595282 0.010030443 -7.355138e-05 20
#> 250 I250 0 0.02624906 0.0022550299 0.010696622 -1.671882e-04 20
#> 251 I251 NA NA NA NA NA 20
#> 252 I252 0 0.02308065 0.0012930507 0.009611879 -1.087865e-04 6
#> 253 I253 0 0.03050580 -0.0026736094 0.008292099 -9.189255e-05 20
#> 254 I254 NA NA NA NA NA 20
#> 255 I255 NA NA NA NA NA 20
#> 256 I256 NA NA NA NA NA 20
#> 257 I257 NA NA NA NA NA 20
#> 258 I258 NA NA NA NA NA 20
#> 259 I259 NA NA NA NA NA 20
#> 260 I260 NA NA NA NA NA 20
#> 261 I261 0 0.02844510 0.0081460227 0.011216633 -2.636950e-04 20
#> 262 I262 NA NA NA NA NA 20
#> 263 I263 NA NA NA NA NA 20
#> 264 I264 NA NA NA NA NA 20
#> 265 I265 NA NA NA NA NA 20
#> 266 I266 NA NA NA NA NA 20
#> 267 I267 NA NA NA NA NA 20
#> 268 I268 NA NA NA NA NA 20
#> 269 I269 NA NA NA NA NA 20
#> 270 I270 0 0.03035192 0.0014464514 0.011862714 -2.830192e-04 20
#> 271 I271 NA NA NA NA NA 20
#> 272 I272 0 0.02695011 0.0017430743 0.009601149 -1.650526e-04 20
#> 273 I273 NA NA NA NA NA 20
#> 274 I274 NA NA NA NA NA 20
#> 275 I275 NA NA NA NA NA 20
#> 276 I276 0 0.02778075 0.0052638286 0.009266525 -1.614325e-04 20
#> 277 I277 0 0.03140725 0.0081933864 0.009749877 -2.098137e-04 20
#> 278 I278 NA NA NA NA NA 20
#> 279 I279 NA NA NA NA NA 20
#> 280 I280 NA NA NA NA NA 20
#> 281 I281 NA NA NA NA NA 20
#> 282 I282 NA NA NA NA NA 20
#> 283 I283 NA NA NA NA NA 20
#> 284 I284 NA NA NA NA NA 20
#> 285 I285 NA NA NA NA NA 20
#> 286 I286 NA NA NA NA NA 20
#> 287 I287 NA NA NA NA NA 20
#> 288 I288 NA NA NA NA NA 20
#> 289 I289 NA NA NA NA NA 20
#> 290 I290 NA NA NA NA NA 20
#> 291 I291 NA NA NA NA NA 20
#> 292 I292 NA NA NA NA NA 20
#> 293 I293 NA NA NA NA NA 20
#> 294 I294 NA NA NA NA NA 20
#> 295 I295 NA NA NA NA NA 20
#> 296 I296 0 0.02443055 0.0080262858 0.009401551 -4.335803e-05 20
#> 297 I297 NA NA NA NA NA 20
#> 298 I298 0 0.02312165 0.0032494398 0.008884495 -4.695869e-05 20
#> 299 I299 NA NA NA NA NA 20
#> 300 I300 0 0.02657890 0.0027097932 0.008873001 -8.436558e-05 20
#> 301 I301 NA NA NA NA NA 20
#> 302 I302 NA NA NA NA NA 20
#> 303 I303 NA NA NA NA NA 20
#> 304 I304 NA NA NA NA NA 20
#> 305 I305 NA NA NA NA NA 20
#> 306 I306 0 0.02925716 0.0159175613 0.013299350 -1.401820e-04 20
#> 307 I307 NA NA NA NA NA 20
#> 308 I308 NA NA NA NA NA 20
#> 309 I309 NA NA NA NA NA 20
#> 310 I310 0 0.02766912 0.0018875244 0.010464046 -1.876161e-04 12
#> 311 I311 0 0.03160307 0.0066633111 0.010270474 -2.129579e-04 20
#> 312 I312 0 0.02729826 0.0109328294 0.012010530 -1.403695e-04 20
#> 313 I313 NA NA NA NA NA 20
#> 314 I314 NA NA NA NA NA 20
#> 315 I315 NA NA NA NA NA 20
#> 316 I316 NA NA NA NA NA 20
#> 317 I317 NA NA NA NA NA 20
#> 318 I318 NA NA NA NA NA 20
#> 319 I319 NA NA NA NA NA 20
#> 320 I320 NA NA NA NA NA 20
#> 321 I321 NA NA NA NA NA 20
#> 322 I322 0 0.02470391 0.0061831329 0.009585017 -1.207477e-04 20
#> 323 I323 NA NA NA NA NA 20
#> 324 I324 NA NA NA NA NA 20
#> 325 I325 0 0.02503480 0.0048945000 0.009416265 -1.335735e-04 20
#> 326 I326 NA NA NA NA NA 20
#> 327 I327 0 0.02872619 0.0070958359 0.009976594 -1.995808e-04 20
#> 328 I328 NA NA NA NA NA 20
#> 329 I329 NA NA NA NA NA 20
#> 330 I330 NA NA NA NA NA 20
#> 331 I331 0 0.02942522 0.0042816626 0.009130054 -1.185105e-04 20
#> 332 I332 NA NA NA NA NA 20
#> 333 I333 NA NA NA NA NA 20
#> 334 I334 0 0.02451207 0.0005583847 0.009003879 -1.077428e-04 0
#> 335 I335 NA NA NA NA NA 20
#> 336 I336 0 0.02922181 0.0014903850 0.007896971 -7.823376e-05 10
#> 337 I337 0 0.02552149 0.0025541291 0.009890441 -1.501769e-04 20
#> 338 I338 NA NA NA NA NA 20
#> 339 I339 NA NA NA NA NA 20
#> 340 I340 NA NA NA NA NA 20
#> 341 I341 NA NA NA NA NA 20
#> 342 I342 NA NA NA NA NA 20
#> 343 I343 NA NA NA NA NA 20
#> 344 I344 NA NA NA NA NA 20
#> 345 I345 NA NA NA NA NA 20
#> 346 I346 NA NA NA NA NA 20
#> 347 I347 0 0.02580272 0.0034345671 0.009221016 -1.352724e-04 20
#> 348 I348 NA NA NA NA NA 20
#> 349 I349 NA NA NA NA NA 20
#> 350 I350 NA NA NA NA NA 20
#> 351 I351 0 0.02680247 -0.0007961721 0.010224271 -1.511985e-04 20
#> 352 I352 NA NA NA NA NA 20
#> 353 I353 NA NA NA NA NA 20
#> 354 I354 0 0.02960216 -0.0012546634 0.010331469 -1.995154e-04 20
#> 355 I355 NA NA NA NA NA 20
#> 356 I356 NA NA NA NA NA 20
#> 357 I357 NA NA NA NA NA 20
#> 358 I358 0 0.02536239 -0.0040880847 0.008369185 -3.006723e-06 20
#> 359 I359 NA NA NA NA NA 20
#> 360 I360 NA NA NA NA NA 20
#>
#> $with_purify$ipd_item
#> [1] 13 26 42 55 58 97 129 138 145 149 181 184 203 236 242 246 252 310 334
#> [20] 336
#>
#> $with_purify$n.iter
#> [1] 20
#>
#> $with_purify$score
#> [1] -3.305816e-01 4.997184e-01 -1.862828e+00 -1.330228e+00 1.759401e+00
#> [6] -1.530740e-01 2.550167e+00 4.679747e-02 9.106693e-01 -1.285723e-02
#> [11] -3.056272e-01 -3.098867e-01 -1.106826e-02 3.280379e-02 4.435253e-01
#> [16] 3.946956e-01 -3.392322e-01 -3.831420e-01 1.489449e-01 4.321907e-01
#> [21] 1.240816e+00 6.555510e-01 -3.479303e-01 -1.899698e+00 1.069704e-02
#> [26] 7.090942e-01 -1.344388e+00 -3.852688e-01 -5.588760e-01 -1.832554e+00
#> [31] -1.322405e-01 -4.155838e-01 1.474098e+00 1.162671e+00 -1.462899e+00
#> [36] -7.595552e-01 1.488755e-01 -5.151589e-01 2.614092e-01 4.353011e-01
#> [41] 9.290722e-01 -1.502359e+00 1.188090e+00 1.799139e-01 -1.603497e+00
#> [46] 1.240232e+00 -7.106960e-01 -8.361715e-01 -1.187060e+00 -8.441683e-01
#> [51] -2.204196e+00 9.036920e-01 2.518446e+00 -2.213624e+00 5.704597e-02
#> [56] 2.688722e-01 -6.593243e-01 -6.917042e-02 -9.266265e-02 6.448842e-02
#> [61] 2.239023e+00 -3.679433e-01 6.155244e-02 -7.278385e-01 -5.168553e-01
#> [66] 1.675696e-01 -2.016226e+00 -9.454619e-01 8.669211e-01 -1.068269e+00
#> [71] 8.745364e-01 3.326973e-02 -3.336624e-03 5.536995e-01 1.362706e+00
#> [76] 2.327784e-01 -2.093647e+00 4.118215e-01 1.973434e+00 3.839035e-01
#> [81] 2.956502e+00 8.681711e-01 -2.534982e-01 -1.954844e+00 -1.285215e+00
#> [86] -1.225344e+00 7.423862e-03 1.599493e+00 -1.897700e+00 -7.467154e-01
#> [91] -2.865034e+00 -6.673564e-01 1.286591e+00 1.118362e+00 -3.287833e-01
#> [96] 2.257974e-01 9.433099e-01 -9.478421e-01 -3.737646e-03 -4.481875e-01
#> [101] 1.927271e+00 1.812211e+00 -3.434263e-01 -9.864655e-01 -9.777317e-01
#> [106] 1.085535e+00 -1.077457e+00 1.501068e+00 -2.514365e+00 -2.405684e-01
#> [111] -1.907764e+00 8.548865e-01 1.044173e+00 -7.210913e-01 -3.536230e-01
#> [116] 1.884550e-01 -1.006065e+00 -2.783930e+00 -9.164759e-01 8.084014e-02
#> [121] 6.573498e-01 -8.149472e-01 2.193507e+00 -1.005620e+00 -1.086745e+00
#> [126] 9.751014e-02 -1.252133e+00 2.571090e+00 -2.668425e-01 3.827680e-01
#> [131] -2.030013e-01 1.623758e+00 -1.229334e+00 7.921849e-01 -2.004078e-01
#> [136] -6.683697e-01 7.093690e-01 -1.184864e+00 4.925621e-01 6.242468e-01
#> [141] -1.092592e+00 4.930798e-01 8.147239e-01 -4.288366e-01 -3.329196e-01
#> [146] -1.472439e+00 2.773635e+00 -1.377702e+00 6.205958e-01 1.578404e+00
#> [151] -8.225996e-01 2.044881e+00 -9.503566e-01 1.930226e+00 1.133781e-01
#> [156] 1.953051e-01 1.608056e+00 1.350667e+00 5.337090e-01 1.491287e+00
#> [161] -3.070479e-01 -5.048103e-01 -3.988234e-02 2.143097e-01 5.459099e-01
#> [166] -3.008332e-01 1.065958e+00 1.695707e-01 -1.688984e+00 7.861688e-01
#> [171] 1.028007e+00 1.086922e-02 4.373680e-01 1.579166e+00 -1.982977e+00
#> [176] 3.154395e-01 -1.357283e+00 -4.773938e-01 -3.308549e-01 5.192138e-01
#> [181] -3.850069e-01 1.004646e+00 1.939879e-02 -6.830665e-01 -1.149228e+00
#> [186] 1.309164e+00 1.125589e+00 8.954748e-02 1.190973e+00 2.390195e+00
#> [191] -1.831850e+00 -1.707225e-01 7.767254e-01 4.336270e-01 8.434275e-02
#> [196] 8.599817e-01 -1.275237e-01 -1.198701e+00 2.728595e+00 1.174242e+00
#> [201] 2.618167e+00 1.798487e-01 1.785812e+00 -7.616680e-01 1.580620e-01
#> [206] 1.711881e+00 1.901504e+00 2.374864e-01 -4.096424e-01 4.125904e-01
#> [211] 1.654517e+00 -1.895018e-01 -9.795736e-01 6.567259e-01 1.008443e-02
#> [216] -1.022745e-01 3.186616e-01 9.975935e-01 -3.200579e-01 -1.220928e-01
#> [221] -1.195049e-02 3.337712e-01 -1.592352e+00 -1.092762e+00 -8.200355e-01
#> [226] -3.057698e-02 8.321306e-01 4.123018e-01 6.953061e-01 -7.540830e-03
#> [231] -1.009830e+00 4.927484e-01 3.356485e-01 1.938731e+00 8.147065e-01
#> [236] 9.721567e-01 7.261872e-01 5.658334e-01 -4.350226e-01 -4.275530e-01
#> [241] -2.230929e+00 -1.377239e-01 7.625292e-01 -1.144254e+00 1.491595e+00
#> [246] -9.775052e-01 -1.054814e-01 1.864919e+00 4.104473e-01 1.954943e+00
#> [251] 2.803430e-01 1.048663e-01 -9.173446e-01 1.158870e+00 3.865123e-01
#> [256] -1.683436e+00 -1.567761e-01 6.777972e-01 -8.590997e-02 4.235408e-01
#> [261] 3.836441e-01 -7.102779e-01 3.481902e-01 -1.573039e-01 1.031852e+00
#> [266] -5.947241e-02 9.008832e-01 5.932208e-01 5.055359e-01 1.669622e-01
#> [271] -1.080872e+00 -3.005340e-01 6.538572e-01 3.556111e-01 -2.042271e+00
#> [276] -1.906073e-01 -3.811076e-01 5.498633e-01 -2.453771e+00 -3.657963e-01
#> [281] 1.445365e+00 1.074582e-01 2.154900e-01 -4.599732e+00 9.875940e-01
#> [286] 1.361774e+00 9.165039e-01 1.096785e-02 1.020655e+00 7.094101e-02
#> [291] 5.217189e-02 -3.307402e-01 1.226051e+00 6.168077e-01 -9.271501e-02
#> [296] 2.343038e+00 -4.761509e-01 7.049759e-01 -3.982226e-01 -1.511890e+00
#> [301] 8.756906e-01 1.080057e+00 3.542177e-01 1.169629e+00 -5.250408e-01
#> [306] 1.223500e+00 7.593881e-01 -1.511014e-01 -1.154119e+00 2.159111e-01
#> [311] -1.273772e+00 7.669512e-01 -6.535146e-01 -1.651084e+00 3.664708e-01
#> [316] 1.089391e+00 4.997922e-01 5.417351e-01 5.232761e-01 1.488472e-01
#> [321] -1.377447e+00 -9.043503e-02 -1.058141e+00 8.646188e-01 -1.217483e-01
#> [326] -7.136387e-01 -4.011486e-01 1.146509e+00 5.735630e-01 1.366564e-01
#> [331] -1.244204e-01 -7.428283e-01 -1.575829e+00 -6.387546e-01 -3.751451e-02
#> [336] -1.057721e+00 1.226201e+00 -2.013415e+00 4.738311e-01 -7.686756e-01
#> [341] -9.984370e-01 -6.260714e-01 -4.395572e-01 1.253003e+00 -2.609551e-01
#> [346] -1.728313e+00 -1.007790e+00 4.274797e-01 -4.781795e-01 2.440895e+00
#> [351] -1.151238e+00 2.053183e-01 8.177010e-01 -8.911530e-01 1.110448e+00
#> [356] -5.552722e-01 -2.306168e-02 -1.116667e+00 -1.367344e+00 -8.540232e-02
#> [361] 9.525218e-01 1.476594e-01 -1.082250e-01 -4.637944e-02 -1.144883e+00
#> [366] 3.636980e-01 -1.653549e+00 3.514631e-01 5.786256e-01 3.026694e-01
#> [371] 2.249348e+00 -5.120245e-02 6.371425e-02 -5.825422e-01 -1.717620e+00
#> [376] 1.197647e-01 -1.226387e-01 2.007045e+00 2.379313e+00 -7.338837e-01
#> [381] -1.063144e-01 3.518800e-01 -1.020734e+00 3.234023e-01 -5.970146e-01
#> [386] 4.225537e-01 -4.542503e-01 -7.932940e-01 -6.524511e-01 -6.820427e-01
#> [391] 1.741998e-01 -2.093015e-01 -4.638160e-01 -1.259166e-01 3.345796e-01
#> [396] 6.486609e-02 3.590915e-02 -1.147962e+00 3.339613e-01 -9.400103e-01
#> [401] -6.611492e-01 -8.577389e-01 -6.701001e-01 -6.679446e-02 -8.564974e-01
#> [406] -1.441216e-01 6.847868e-02 1.597742e-01 -9.487216e-01 4.989253e-01
#> [411] 3.283729e-01 -6.185802e-01 2.548729e-01 -7.665711e-01 -7.129857e-01
#> [416] 5.148290e-01 -5.707116e-01 6.941420e-01 1.887569e+00 4.824122e-01
#> [421] -2.583562e-02 -1.525024e-01 -6.859421e-01 1.400968e+00 -5.292438e-01
#> [426] 2.541956e-01 -2.155078e-02 -5.520520e-01 4.714212e-01 1.862672e-01
#> [431] -2.127491e-01 3.314922e-01 3.004709e-01 -1.465873e-01 1.717582e+00
#> [436] -5.077380e-01 -3.358856e-01 -1.591209e-01 -1.049447e-01 -5.119915e-02
#> [441] 8.762630e-01 3.664569e-01 8.767381e-01 -2.061247e+00 -4.472971e-01
#> [446] 1.031938e-01 -1.620260e+00 -2.246334e+00 1.163224e+00 -1.072807e+00
#> [451] 4.216912e-02 1.163816e+00 -2.302133e-01 -1.978789e+00 1.732390e-01
#> [456] -1.023452e+00 9.407547e-02 -1.916410e-02 -3.057212e-01 -4.557122e-01
#> [461] -1.093109e+00 -4.510246e-01 1.045560e-01 2.132659e-01 -1.540681e+00
#> [466] 2.995866e-01 -8.194306e-01 1.169245e-01 2.536752e+00 4.007999e-01
#> [471] -7.426597e-02 6.258945e-02 -1.687627e+00 2.545938e+00 1.055544e+00
#> [476] 9.848431e-01 -4.451924e-01 2.030158e+00 1.279828e+00 2.808521e-01
#> [481] -1.581960e-01 -1.650920e+00 8.489761e-01 6.132610e-01 4.155775e-01
#> [486] -1.780556e-01 6.968857e-01 -6.134510e-02 -8.411998e-02 5.160396e-01
#> [491] -4.839674e-01 5.200607e-01 3.160631e-01 -1.935366e-01 -2.281486e-01
#> [496] 5.282877e-01 2.468908e-01 5.667004e-01 -7.182878e-01 -5.121717e-01
#> [501] -5.718124e-01 6.285674e-01 -1.036124e+00 3.811471e-01 4.927279e-01
#> [506] -2.204493e-02 -5.595506e-01 -1.026978e+00 1.219491e+00 -3.183044e-01
#> [511] 3.604639e-01 4.137216e-01 1.084994e+00 1.861277e+00 1.723531e+00
#> [516] -3.608830e-01 9.029024e-01 9.271360e-01 8.224425e-01 -7.732476e-01
#> [521] 1.663137e+00 -7.322716e-01 1.654338e+00 1.535304e+00 -3.564528e-01
#> [526] 1.370360e+00 -1.311663e+00 1.054582e+00 8.364130e-01 -1.142557e-01
#> [531] 4.910846e-01 1.344018e+00 -2.890642e-02 1.064357e+00 1.358693e+00
#> [536] -5.470843e-01 -1.467043e+00 4.259499e-02 1.477644e+00 1.563668e-01
#> [541] -1.912359e+00 -2.667858e-01 -2.499333e-01 -8.376923e-01 -1.420382e+00
#> [546] -6.578996e-01 -6.049868e-02 4.954883e-01 1.764359e-01 -9.491080e-01
#> [551] 1.003052e+00 -5.032445e-02 -1.039010e+00 1.825080e+00 -1.091848e+00
#> [556] 1.344833e+00 -1.062772e+00 9.823035e-01 -3.066937e-01 1.218757e+00
#> [561] 1.775036e-01 8.640968e-01 9.350893e-01 -3.589739e-01 2.017554e+00
#> [566] 8.418657e-01 -9.901298e-02 -6.033551e-01 2.325784e-01 -4.883133e-02
#> [571] 1.794671e+00 3.056705e-01 -1.819456e-01 7.313462e-01 4.086593e-02
#> [576] 4.078826e-01 -4.076181e-01 2.127672e-01 9.038489e-01 -1.026796e-01
#> [581] -2.945746e-01 4.031943e-01 -2.236001e+00 6.187038e-02 -4.946116e-01
#> [586] -1.169923e+00 -1.178081e-01 -3.071786e-01 -1.664316e+00 6.280117e-01
#> [591] 9.370155e-01 7.607484e-01 1.329724e+00 1.786119e+00 -2.973495e-01
#> [596] -3.071576e-01 4.519704e-01 1.216068e+00 -1.528301e+00 1.728954e-01
#> [601] -2.335096e-01 4.148878e-01 6.168520e-01 -6.180434e-01 -1.204947e+00
#> [606] 3.883131e-01 -4.656479e-01 6.577887e-02 -1.116456e+00 -3.019481e-01
#> [611] 5.551582e-02 -4.582278e-01 -5.391339e-01 -1.745387e-01 -1.160794e+00
#> [616] 5.158053e-01 1.380602e+00 -6.825254e-01 -3.692090e-02 -6.714216e-01
#> [621] 7.413806e-01 -1.439298e+00 1.810945e+00 9.164847e-01 3.171357e-01
#> [626] -4.081902e-01 8.281762e-01 8.084507e-02 -4.997108e-01 -1.573957e-01
#> [631] 8.091608e-01 1.269030e+00 1.353168e+00 7.140766e-01 -3.357100e-01
#> [636] 1.515528e+00 2.578571e-01 -3.415453e-01 -5.447791e-01 1.130131e+00
#> [641] -2.403601e-01 4.828118e-01 -4.197291e-01 8.529838e-01 1.011658e+00
#> [646] -1.656527e-01 1.539746e+00 -5.948791e-01 -3.930835e-01 -2.139793e+00
#> [651] -6.013670e-01 3.149629e-01 -1.083131e+00 5.376879e-01 1.087787e-01
#> [656] 1.068465e-01 -6.523147e-02 -5.000000e+00 -1.246608e+00 -3.750857e-01
#> [661] -1.046344e+00 -3.103510e+00 7.609072e-01 5.218849e-01 -7.008830e-01
#> [666] 1.730721e+00 -1.126567e+00 -5.689465e-01 7.376122e-01 1.674198e+00
#> [671] 1.417324e+00 -5.589831e-01 -5.656976e-01 -2.308068e+00 9.101060e-02
#> [676] 9.779629e-01 -6.680694e-01 1.362523e+00 -7.030006e-01 1.155792e+00
#> [681] -6.352101e-01 -1.112379e+00 -2.092115e-02 -7.355342e-01 2.928180e-01
#> [686] 7.221397e-01 -1.803831e+00 1.282647e+00 -2.208727e-01 4.343727e-01
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#> [1876] -1.689432e+00 6.302888e-01 -4.459681e-01 -3.973792e-01 4.022074e-01
#> [1881] 1.018614e-01 7.706309e-01 1.563544e+00 2.084183e-01 -8.821408e-01
#> [1886] 2.348486e+00 2.014935e-01 6.125414e-01 -7.205818e-01 -1.184413e+00
#> [1891] 2.730688e-01 -1.058259e+00 -1.909014e-01 5.900405e-01 -1.753503e+00
#> [1896] 2.245068e+00 -1.504966e+00 -2.195615e-01 1.143499e+00 -1.269348e+00
#> [1901] 3.349923e-01 7.339790e-02 -1.021180e+00 7.534816e-01 1.826343e+00
#> [1906] -6.289093e-01 6.526535e-02 -1.236040e+00 -3.615539e-01 6.343808e-01
#> [1911] 6.934417e-01 -9.773836e-01 -4.564454e-01 1.568885e+00 7.016124e-01
#> [1916] -1.637904e-01 -2.205010e-01 1.292109e+00 -1.123072e+00 -7.548138e-01
#> [1921] 1.586423e+00 -1.268790e+00 -3.229614e-01 1.172809e+00 8.875988e-03
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#> [1931] 1.511391e-01 -6.208151e-01 1.038168e+00 5.499166e-01 4.668746e-01
#> [1936] 1.720463e+00 1.689294e+00 2.554110e-01 5.547326e-01 7.714289e-01
#> [1941] -5.466174e-02 1.544792e+00 -1.267678e+00 3.090430e-01 1.113065e+00
#> [1946] -1.129536e+00 -2.816427e-01 9.115526e-01 1.711355e+00 3.657869e-01
#> [1951] 2.225967e-01 -5.050289e-01 1.293448e+00 3.735295e-01 -1.039543e+00
#> [1956] 2.920219e-01 -2.643248e-01 -2.584979e-01 1.865228e+00 -4.608128e-01
#> [1961] 5.709197e-01 9.216790e-01 1.380912e+00 -1.878432e-01 -1.194358e+00
#> [1966] 7.039621e-01 -3.545306e-01 1.842210e+00 1.005510e+00 -7.409658e-01
#> [1971] 1.263182e+00 -5.598631e-01 -6.632933e-01 8.921848e-01 -1.431994e+00
#> [1976] -8.397335e-01 5.544667e-01 1.967957e-02 4.579427e-01 9.297046e-01
#> [1981] 1.823095e+00 2.062752e-01 7.946838e-01 -5.462312e-01 -2.872020e-01
#> [1986] 8.931775e-01 -9.570436e-02 8.035150e-01 -1.418212e+00 -1.603298e+00
#> [1991] -2.748647e-01 9.923305e-01 -6.742495e-01 5.591027e-01 -1.310754e-01
#> [1996] -7.805036e-01 -1.392396e+00 -1.053108e+00 2.394498e+00 6.751703e-01
#> [2001] -3.517961e-01 -8.076636e-01 4.728455e-01 -3.858457e-01 -1.152562e+00
#> [2006] 1.660779e+00 -7.168485e-01 -5.019552e-02 7.466799e-01 -4.782842e-01
#> [2011] 1.001178e+00 -2.190065e-01 -1.448684e+00 -9.487900e-01 1.799103e-01
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#> [5676] 8.821662e-01 -6.635003e-01 7.172655e-01 -2.460875e+00 -8.452448e-02
#> [5681] 1.461017e+00 1.813957e+00 -6.183938e-01 9.278296e-01 8.455758e-01
#> [5686] 6.645204e-01 -2.312303e-01 -4.823456e-01 6.230309e-01 6.853012e-01
#> [5691] 4.993195e-01 -3.779953e-01 -1.654788e-01 -5.171878e-01 -3.888758e-01
#> [5696] 3.422452e-01 -7.693538e-01 -1.530443e-01 1.519881e+00 7.890876e-01
#> [5701] -2.768226e-01 2.303238e+00 8.687905e-01 -1.330620e+00 2.338648e+00
#> [5706] -2.803382e-01 -7.636621e-01 -1.290570e+00 -2.647408e+00 1.239824e+00
#> [5711] -2.868604e-01 3.148150e-02 -3.992562e-01 -3.143705e-01 3.539135e-01
#> [5716] 4.573164e-02 -2.344288e+00 1.072202e+00 7.537699e-01 3.665959e-01
#> [5721] 1.762674e+00 -7.555193e-01 -5.974402e-01 -6.711750e-01 1.577695e+00
#> [5726] 6.881126e-01 -3.714499e-01 -1.791831e+00 8.241244e-01 7.740285e-01
#> [5731] 7.124529e-01 -1.810664e+00 4.439236e-03 -5.560273e-01 2.689819e-01
#> [5736] -1.646747e-02 2.905541e+00 -1.629134e+00 1.320355e+00 -1.085876e-01
#> [5741] -2.644895e+00 -4.336388e-01 4.865704e-03 2.422953e+00 6.208626e-01
#> [5746] 3.723167e-01 8.907333e-01 -4.661148e-01 1.411961e+00 -9.510434e-02
#> [5751] -8.891762e-01 -1.943469e+00 -9.139404e-01 1.027431e+00 2.689602e-01
#> [5756] -1.668667e+00 1.271415e+00 -8.612312e-02 3.163524e-01 6.061620e-02
#> [5761] 3.408867e-01 9.881278e-01 -1.019552e+00 1.744909e+00 1.207824e+00
#> [5766] -1.252364e-01 -5.687141e-01 -3.509216e-01 -7.477502e-03 9.577434e-02
#> [5771] -5.621131e-01 -4.167413e-01 -1.800222e-01 1.265130e+00 8.453323e-01
#> [5776] -5.918604e-01 -1.608417e-01 -4.162077e-01 -6.114937e-01 9.513210e-01
#> [5781] 1.121254e+00 -1.665460e+00 -1.299945e+00 8.710568e-01 -9.361004e-01
#> [5786] 4.771580e-01 -9.602010e-01 1.136884e+00 -1.197602e-01 -3.057314e+00
#> [5791] 9.699469e-01 3.663445e-01 1.247974e+00 5.223041e-02 5.391787e-01
#> [5796] -3.223047e-01 3.566712e-01 -1.913722e+00 6.532197e-01 -6.980978e-01
#> [5801] -8.145246e-01 6.188430e-03 -1.208714e-01 8.789513e-01 -1.621029e+00
#> [5806] 1.271728e+00 1.158808e+00 -9.507921e-02 3.366131e-01 -1.951913e+00
#> [5811] -1.619190e+00 1.096954e-01 -9.152960e-01 -9.358054e-01 1.156515e+00
#> [5816] -6.073402e-02 6.697784e-01 -4.635261e-01 -5.430908e-02 -4.570457e-01
#> [5821] -4.303903e-01 -5.284918e-01 -3.139151e-01 -6.010404e-01 8.081705e-01
#> [5826] 5.924862e-02 -7.204761e-01 1.629445e+00 2.396823e+00 7.881589e-01
#> [5831] -5.626772e-01 -3.334007e-01 1.803244e+00 1.607244e-01 -6.407815e-01
#> [5836] 1.493874e+00 -2.020644e-02 9.114190e-01 1.612758e+00 -4.314484e-01
#> [5841] 4.214053e-02 2.970625e-01 7.603673e-01 -1.339816e-01 -7.744691e-01
#> [5846] -7.130339e-01 4.492225e-01 -1.344075e+00 -1.087601e+00 -6.840956e-01
#> [5851] 9.237700e-01 -1.182054e+00 7.462063e-01 9.241480e-01 1.184366e+00
#> [5856] 1.823154e+00 1.655590e+00 -1.272898e-01 -2.916665e-01 -8.661762e-01
#> [5861] 1.594446e+00 -9.971000e-01 2.249411e-01 -1.299420e+00 5.506049e-01
#> [5866] 3.064102e-01 2.284627e-01 1.454449e+00 -7.042022e-01 -4.322213e-02
#> [5871] 1.246372e+00 -1.864441e+00 1.339565e-01 3.725045e-01 1.057697e+00
#> [5876] -2.700481e-01 3.128174e-01 1.683707e+00 -1.603099e-01 1.724275e+00
#> [5881] 2.714551e-02 7.638410e-02 -6.215424e-01 1.004691e+00 -9.365436e-02
#> [5886] 2.607959e-01 -1.384308e+00 1.730307e+00 -9.438301e-01 9.136828e-01
#> [5891] -8.395955e-01 1.046153e-02 -2.891918e-01 -1.229638e+00 1.351051e+00
#> [5896] 2.335127e+00 -9.199851e-01 -7.703235e-02 2.588199e+00 5.066813e-01
#> [5901] 2.991242e-01 -6.061885e-01 1.303632e+00 -1.417059e+00 -1.506521e-01
#> [5906] 1.853854e+00 6.622403e-01 6.911901e-01 -1.531472e+00 1.286836e-01
#> [5911] 7.270584e-01 -9.041392e-01 3.537540e-01 -5.565721e-01 4.229520e-02
#> [5916] -2.679514e-03 -1.003538e+00 -3.552064e-01 -8.124678e-01 8.470717e-01
#> [5921] 8.747835e-01 4.662128e-01 1.413525e+00 7.403875e-01 5.699820e-01
#> [5926] -4.569729e-01 1.695516e+00 -1.727212e+00 -3.664017e-01 5.614994e-01
#> [5931] 8.851678e-01 8.070020e-01 -5.693637e-02 -1.067834e-01 1.093074e+00
#> [5936] 2.487325e-01 -1.291551e+00 1.064335e+00 1.260395e+00 1.236788e-01
#> [5941] -5.347817e-01 7.700638e-01 2.723635e-02 -1.189519e+00 -6.050583e-01
#> [5946] -1.086348e+00 1.069660e+00 -2.247307e-01 -1.711995e+00 -1.515679e+00
#> [5951] 3.641589e-01 -4.284513e-02 -1.439844e+00 5.381675e-01 -9.346434e-03
#> [5956] -4.672201e-01 -2.888719e-01 5.114758e-01 -1.185641e+00 -1.055037e+00
#> [5961] 2.773030e-01 -6.691477e-01 -9.363729e-02 -9.640170e-01 1.983158e+00
#> [5966] -9.673592e-02 4.808038e-01 2.410982e-01 -2.331889e-01 1.555732e+00
#> [5971] 1.271770e-01 -2.094435e-01 -3.991405e-01 9.053952e-01 6.417971e-01
#> [5976] -2.042990e+00 1.299449e+00 -1.070124e+00 1.106520e+00 -4.356180e-01
#> [5981] 9.858472e-01 4.911965e-02 -3.764889e-02 6.231511e-01 1.329575e+00
#> [5986] -3.562115e-01 -1.382699e-01 -1.455744e+00 -1.205222e+00 1.471091e-03
#> [5991] 3.340481e-01 1.013749e+00 -7.175716e-01 -9.492008e-01 6.532982e-01
#> [5996] 6.541346e-01 3.919637e-01 -1.209161e+00 8.645880e-01 -1.859456e-01
#>
#> $with_purify$complete
#> [1] TRUE
#>
#>
#> $alpha
#> [1] 0.05
#>
#> $call
#> ripd.default(x = simIPD$item_par, data = data, score = score,
#> group = group, focal.name = 1, item.skip = simIPD$item.skip,
#> D = 1.7, alpha = 0.05, purify = TRUE, purify.by = "ripdrs",
#> max.iter = 30, method = "ML", range = c(-5, 5))
#>
#> attr(,"class")
#> [1] "ripd"
## Step 4. Compare detected items to ground truth
detected <- ripd_result$with_purify$ipd_item
cat("Truly drifted items (ground truth):", simIPD$ipd_item, "\n")
#> Truly drifted items (ground truth): 26 42 55 58 97 129 138 145 149 181 184 203 242 246 252 310 334 336
cat("RIPD-detected items: ", detected, "\n")
#> RIPD-detected items: 13 26 42 55 58 97 129 138 145 149 181 184 203 236 242 246 252 310 334 336
cat("True positives:", sum(detected %in% simIPD$ipd_item), "of",
length(simIPD$ipd_item), "\n")
#> True positives: 18 of 18
## -- Note on reference group size -----------------------------------------
## This example uses a 1F reference group (n_ref = n_foc = 3,000).
## In practice, a larger reference group (3F-8F) substantially improves
## detection power. To create a 3F reference group, replicate the focal
## theta estimates and re-run the CAT simulation with original parameters:
##
## theta_3F <- rep(simIPD$foc_score, times = 3) # 9,000 examinees
## resp_3F <- simdat(x = simIPD$item_par, theta = theta_3F, D = 1.7)
## # ... then run CAT and call ripd() with the larger reference group
## -------------------------------------------------------------------------
# }