Description: Dedicated to the analysis of CGH (Comparative Genomic Hybridization) array profiles using segmentation models. 'cghseg' package is intended to detect breakpoints from CGH profiles. It can handle both single and multiple profiles analysis, to perform segmentation, normalization and calling. Methods for joint segmentation are described in : Picard and al. (2011), <doi:10.1093/biostatistics/kxq076>.

Title: L1-Penalized Censored Gaussian Graphical Models
Description: The l1-penalized censored Gaussian graphical model (cglasso) 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.
Packaged: 2018-09-10 12:32:39 UTC; augugliaro

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.
Packaged: 2018-09-19 06:38:47 UTC; luigiaugugliaro

Packaged: 2019-06-09 10:37:26 UTC; luigiaugugliaro

Packaged: 2020-07-21 06:40:18 UTC; luigiaugugliaro

Title: Conditional Graphical LASSO for Gaussian Graphical Models with
Authors@R: c(person(given = "Luigi", family = "Augugliaro", email = "luigi.augugliaro@unipa.it", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4603-7541")),
person(given = "Gianluca", family = "Sottile", role = "aut", comment = c(ORCID = "0000-0001-9347-7251")),
person(given = "Ernst C.", family = "Wit", role = "aut", comment = c(ORCID = "0000-0002-3671-9610")),
person(given = "Veronica", family = "Vinciotti", role = "aut", comment = c(ORCID = "0000-0002-2625-7977")))
Description: Conditional graphical lasso (cglasso) 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, cglasso 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.
Author: Luigi Augugliaro [aut, cre] (<https://orcid.org/0000-0002-4603-7541>),
Packaged: 2021-01-04 16:04:12 UTC; luigiaugugliaro