sharp (version 1.4.7)

Stable: Stable results

Description

Extracts stable results for stability selection or consensus clustering.

Usage

Stable(stability, argmax_id = NULL, linkage = "complete")
SelectedVariables(stability, argmax_id = NULL)
Adjacency(stability, argmax_id = NULL)
Clusters(stability, linkage = "complete", argmax_id = NULL)

Value

A binary vector or matrix encoding the selection status (1 if selected, 0 otherwise) in stability selection or stable cluster membership in consensus clustering.

Arguments

stability

output of VariableSelection, BiSelection, GraphicalModel or Clustering.

argmax_id

optional indices of hyper-parameters. If argmax_id=NULL, the calibrated hyper-parameters are used.

linkage

character string indicating the type of linkage used in hierarchical clustering to define the stable clusters. Possible values include "complete", "single" and "average" (see argument "method" in hclust for a full list).

See Also

VariableSelection, BiSelection, GraphicalModel, Clustering

Examples

# \donttest{
# Variable selection
set.seed(1)
simul <- SimulateRegression(pk = 20)
stab <- VariableSelection(xdata = simul$xdata, ydata = simul$ydata)
SelectedVariables(stab)
Stable(stab)

# Graphical model
set.seed(1)
simul <- SimulateGraphical(pk = 10)
stab <- GraphicalModel(xdata = simul$data)
Adjacency(stab)
Stable(stab)

# Clustering
set.seed(1)
simul <- SimulateClustering(
  n = c(30, 30, 30),
  nu_xc = 1
)
stab <- Clustering(xdata = simul$data)
Clusters(stab)
Stable(stab)
# }