onefold.chooser function

one fold cross-validation for specifying threshold r

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)