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cglasso  

Conditional Graphical LASSO for Gaussian Graphical Models with Censored and Missing Values
View on CRAN: Click here


Download and install cglasso package within the R console
Install from CRAN:
install.packages("cglasso")

Install from Github:
library("remotes")
install_github("cran/cglasso")

Install by package version:
library("remotes")
install_version("cglasso", "2.0.7")



Attach the package and use:
library("cglasso")
Maintained by
Luigi Augugliaro
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-09-15
Latest Update: 2023-01-17
Description:
Conditional graphical lasso estimator is an extension of the graphical lasso proposed to estimate the conditional dependence structure of a set of p response variables given q predictors. This package provides suitable extensions developed to study datasets with censored and/or missing values. Standard conditional graphical lasso is available as a special case. Furthermore, the package provides an integrated set of core routines for visualization, analysis, and simulation of datasets with censored and/or missing values drawn from a Gaussian graphical model. Details about the implemented models can be found in Augugliaro et al. (2023) , Augugliaro et al. (2020b) , Augugliaro et al. (2020a) , Yin et al. (2001) and Stadler et al. (2012) .
How to cite:
Luigi Augugliaro (2018). cglasso: Conditional Graphical LASSO for Gaussian Graphical Models with Censored and Missing Values. R package version 2.0.7, https://cran.r-project.org/web/packages/cglasso
Previous versions and publish date:
1.0.0 (2018-09-15 01:22), 1.1.0 (2018-09-19 09:30), 1.1.1 (2019-06-11 09:20), 1.1.2 (2020-07-21 09:10), 2.0.0 (2021-01-05 17:20), 2.0.1 (2021-01-11 17:00), 2.0.2 (2021-01-21 18:20), 2.0.3 (2021-04-06 17:50), 2.0.4 (2021-04-09 10:20), 2.0.5 (2022-05-27 14:40), 2.0.6 (2023-01-17 18:00)
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