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. (2020b) <doi: 10.1007/s11222-020-09945-7>, Augugliaro et al. (2020a) <doi: 10.1093/biostatistics/kxy043>, Yin et al. (2001) <doi: 10.1214/11-AOAS494> and Stadler et al. (2012) <doi: 10.1007/s11222-010-9219-7>.
|Author||Luigi Augugliaro [aut, cre] (<https://orcid.org/0000-0002-4603-7541>), Gianluca Sottile [aut] (<https://orcid.org/0000-0001-9347-7251>), Ernst C. Wit [aut] (<https://orcid.org/0000-0002-3671-9610>), Veronica Vinciotti [aut] (<https://orcid.org/0000-0002-2625-7977>)|
|Maintainer||Luigi Augugliaro <firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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