PKLMtest: PKLMtest: compute a p-value for testing MCAR

In PKLMtest: Classification Based MCAR Test

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)

PKLMtest documentation built on Nov. 5, 2021, 5:07 p.m.