onefold.chooser: one fold cross-validation for specifying threshold r

In clusterMI: Cluster Analysis with Missing Values by Multiple Imputation

one fold cross-validation for specifying threshold r

Description

one fold cross-validation for specifying threshold r

Usage

onefold.chooser(
  data.train.k,
  data.test.k,
  jj,
  grid.r,
  nb.clust,
  nnodes,
  sizeblock,
  method.select,
  B,
  modelNames,
  K,
  path.outfile,
  nbvarused
)

Arguments

data.train.k	a train set
data.test.k	a test set
jj	name of the outcome used for variable selection
grid.r	a grid for the tuning parameter r
nb.clust	number of clusters
sizeblock	number of sampled variables at each iteration
method.select	variable selection method
B	number of iterations
modelNames	mixture model specification for imputation of subsets
K	number of fold
path.outfile	a path for message redirection
nbvarused	a maximal number of selected variables (can be required with a large number of variables)

clusterMI documentation built on April 4, 2025, 12:55 a.m.