| Type: | Package |
| Title: | Classification Based MCAR Test |
| Version: | 1.0.1 |
| Description: | Implementation of a KL-based (Kullback-Leibler) test for MCAR (Missing Completely At Random) in the context of missing data as introduced in Michel et al. (2021) <doi:10.48550/arXiv.2109.10150>. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.1 |
| Depends: | parallel, stats, ranger |
| NeedsCompilation: | no |
| Packaged: | 2021-11-05 15:14:27 UTC; lorismichel |
| Author: | Meta-Lina Spohn [aut, cre], Loris Michel [aut], Jeffrey Naef [aut] |
| Maintainer: | Meta-Lina Spohn <metalina.spohn@stat.math.ethz.ch> |
| Repository: | CRAN |
| Date/Publication: | 2021-11-05 16:10:02 UTC |
PKLMtest: compute a p-value for testing MCAR
Description
PKLMtest: compute a p-value for testing MCAR
Usage
PKLMtest(
X,
num.proj = 300,
num.trees.per.proj = 10,
nrep = 500,
min.node.size = 10,
size.resp.set = 2,
compute.partial.pvals = FALSE,
...
)
Arguments
X |
a numeric matrix containing missing values encoded as NA, the data. |
num.proj |
a positive integer specifying the number of projections to consider for the score. |
num.trees.per.proj |
a positive integer, the number of trees per projection. |
nrep |
a positive integer, the number of permutations. |
min.node.size |
a positive number, the minimum number of nodes in a tree. |
size.resp.set |
an integer (>= 2), maximum number of classes allowed to be compared in each projection. |
compute.partial.pvals |
a boolean, indicate if partial p-values shopuld be computed as well. |
... |
additional parameters. |
Value
a numeric value, the p-value(s) for the MCAR test, the first value is always the global p-value and if compute.partial.pvals is set to TRUE, the next values are the partial p-values for the relative importance of each variable.
Examples
n <- 100
X <- cbind(rnorm(n),rnorm(n))
X.NA <- X
X.NA[,1] <- ifelse(stats::runif(n)<=0.2, NA, X[,1])
pval <- PKLMtest(X.NA, num.proj = 5)
Generate the test statistic
Description
Generate the test statistic
Usage
genU(st, lab)
Arguments
st |
a ranger forest object. |
lab |
an integer value containing the class labels |
Value
the likelihood-based test statistic
Truncation of probability
Description
Truncation of probability
Usage
truncProb(p)
Arguments
p |
a numeric value between 0 and 1 to be truncated |
Value
a numeric value with truncated probabilities