BlockLambdaGrid: Multi-block grid

In sharp: Stability-enHanced Approaches using Resampling Procedures

Multi-block grid

Description

Generates a matrix of parameters controlling the sparsity of the underlying selection algorithm for multi-block calibration.

Usage

BlockLambdaGrid(Lambda, lambda_other_blocks = NULL)

Arguments

Lambda	vector or matrix of penalty parameters.
lambda_other_blocks	optional vector of penalty parameters to use for other blocks in the iterative multi-block procedure.

Value

A list with:

Lambda

a matrix of (block-specific) penalty parameters. In multi-block stability selection, rows correspond to sets of penalty parameters and columns correspond to different blocks.

Sequential_template

logical matrix encoding the type of procedure for data with multiple blocks in stability selection graphical modelling. For multi-block estimation, each block is calibrated separately while others blocks are weakly penalised (TRUE only for the block currently being calibrated and FALSE for other blocks). Other approaches with joint calibration of the blocks are allowed (all entries are set to TRUE).

See Also

GraphicalModel

Examples

# Multi-block grid
Lambda <- matrix(
  c(
    0.8, 0.6, 0.3,
    0.5, 0.4, 0.2,
    0.7, 0.5, 0.1
  ),
  ncol = 3, byrow = TRUE
)
mygrid <- BlockLambdaGrid(Lambda, lambda_other_blocks = 0.1)

# Multi-parameter grid (not recommended)
Lambda <- matrix(
  c(
    0.8, 0.6, 0.3,
    0.5, 0.4, 0.2,
    0.7, 0.5, 0.1
  ),
  ncol = 3, byrow = TRUE
)
mygrid <- BlockLambdaGrid(Lambda, lambda_other_blocks = NULL)

sharp documentation built on April 11, 2025, 5:44 p.m.