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sglasso (version 1.2.6)

Lasso Method for RCON(V,E) Models

Description

RCON(V, E) models are a kind of restriction of the Gaussian Graphical Models defined by a set of equality constraints on the entries of the concentration matrix. 'sglasso' package implements the structured graphical lasso (sglasso) estimator proposed in Abbruzzo et al. (2014) for the weighted l1-penalized RCON(V, E) model. Two cyclic coordinate algorithms are implemented to compute the sglasso estimator, i.e. a cyclic coordinate minimization (CCM) and a cyclic coordinate descent (CCD) algorithm.

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Version

Install

install.packages('sglasso')

Monthly Downloads

186

Version

1.2.6

License

GPL (>= 2)

Maintainer

Luigi Augugliaro

Last Published

December 3rd, 2023

Functions in sglasso (1.2.6)

plot.sglasso

Plot Method for the Weighted l1-Penalized RCON(V, E) Model
Kh

Extract Sparse Structured Precision Matrices
gplot.sglasso

Plotting Sparse Graphs
neisseria

Neisseria Data Set
klcv

Cross-Validated Kullback-Leibler Divergence
gplot

Plotting Sparse Graph
sglasso-internal

Internal sglasso functions
loglik

Extract Log-Likelihood
plot.klcv

Plot Method for Leave-One-Out Cross-Validated Kullback-Leibler Divergence
fglasso

L1-penalized Factorial Graphical Lasso Model
gplot.fglasso

Plotting Sparse Factorial Dynamic Gaussian Graphical Model
summary.sglasso

Summarizing sglasso Fits
sglasso-package

Lasso Method for RCON(V, E) Models
sglasso

Lasso Method for the RCON(V, E) Models