cglasso: An R Package for Conditional Graphical Lasso Inference with Censored and Missing Values

cglasso: An R Package for Conditional Graphical Lasso Inference with Censored and Missing Values

Sparse graphical models have revolutionized multivariate inference. With the advent of high-dimensional multivariate data in many applied fields, these methods are able to detect a much lower-dimensional structure, often represented via a sparse conditional independence graph. There have been numer...

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Bibliographic Details
Main Authors: Luigi Augugliaro, Gianluca Sottile, Ernst C. Wit, Veronica Vinciotti
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2023-01-01
Series:Journal of Statistical Software
Subjects:
conditional Gaussian graphical models
glasso
high-dimensionality
sparsity
censoring
missing data
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/4335
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https://www.jstatsoft.org/index.php/jss/article/view/4335

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