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MLGL (version 1.0.0)

Multi-Layer Group-Lasso

Description

It implements a new procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data (Grimonprez et al. (2023) ).

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Version

Install

install.packages('MLGL')

Monthly Downloads

208

Version

1.0.0

License

GPL (>= 2)

Maintainer

Quentin Grimonprez

Last Published

March 15th, 2023

Functions in MLGL (1.0.0)

hierarchicalFDR

Hierarchical testing with FDR control

plot.fullProcess

Plot the path obtained from fullProcess function

Obtain a sparse matrix of the coefficients of the path

Plot the path obtained from MLGL function

hierarchicalFWER

Hierarchical testing with FWER control

Group-lasso with overlapping groups

Plot the path obtained from HMT function

Plot the cross-validation obtained from cv.MLGL function

print.fullProcess

plot.stability.MLGL

Plot the stability path obtained from stability.MLGL function

simuBlockGaussian

Simulate multivariate Gaussian samples with block diagonal variance matrix

summary.fullProcess

Object Summaries

Object Summaries

Selection from hierarchical testing with FDR control

Selection from hierarchical testing with FWER control

Object Summaries

Stability Selection for Multi-Layer Group-lasso

predict.cv.MLGL

Predict fitted values from a cv.MLGL object

Predict fitted values from a MLGL object

uniqueGroupHclust

Find all unique groups in hclust results

computeGroupSizeWeight

Compute the group size weight vector with an authorized maximal size

Get coefficients from a cv.MLGL object

bootstrapHclust

Hierarchical Clustering with distance matrix computed using bootstrap replicates

Get coefficients from a MLGL object

Multi-Layer Group-Lasso with cross V-fold validation

Full process of MLGL

Hierarchical Multiple Testing procedure

Multi-Layer Group-Lasso