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cglasso (version 1.1.2)

L1-Penalized Censored Gaussian Graphical Models

Description

The l1-penalized censored Gaussian graphical model is an extension of the graphical lasso estimator developed to handle datasets with censored observations. An EM-like algorithm is implemented to estimate the parameters of the censored Gaussian graphical models.

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Version

Install

install.packages('cglasso')

Monthly Downloads

356

Version

1.1.2

License

GPL (>= 2)

Maintainer

Luigi Augugliaro

Last Published

July 21st, 2020

Functions in cglasso (1.1.2)

cglasso-package

L1-Penalized Censored Gaussian Graphical Model
cglasso-internal

Internal Functions
event

Return the Indicator Matrix from an Object with class ‘datacggm’
glasso

Lasso Estimator for Gaussian Graphical Models
cglasso

Censored Graphical Lasso Estimator
coef

Extract Model Coefficients
MKMEP

Megakaryocyte-Erythroid Progenitors
ebic

Extended Bayesian Information Criterion
aic

Akaike's An Information Criterion
datacggm

Create a Dataset from a Censored Gaussian Graphical Model
summary

Summary Method
scale.datacggm

Scaling and Centering of “datacggm” Objects
rdatacggm

Simulate from a Censored Gaussian Graphical Model
to_graph

Create Undirected Graphs
summary.datacggm

Summarizing Objects of Class ‘cggmdata’
plot

Plot for ‘glasso’ and ‘cglasso’ Object
mle

Maximum Likelihood Estimation
loglik

Extract Log-Likelihood or Q-Function
mglasso

Graphical Lasso Estimator with Missing-at-Random Data