MvBinary: Modelling Multivariate Binary Data with Blocks of Specific One-Factor Distribution

Modelling Multivariate Binary Data with Blocks of Specific One-Factor Distribution. Variables are grouped into independent blocks. Each variable is described by two continuous parameters (its marginal probability and its dependency strength with the other block variables), and one binary parameter (positive or negative dependency). Model selection consists in the estimation of the repartition of the variables into blocks. It is carried out by the maximization of the BIC criterion by a deterministic (faster) algorithm or by a stochastic (more time consuming but optimal) algorithm. Tool functions facilitate the model interpretation.

Package details

AuthorMatthieu Marbac and Mohammed Sedki
MaintainerMohammed Sedki <mohammed.sedki@u-psud.fr>
LicenseGPL (>= 2)
Version1.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("MvBinary")

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MvBinary documentation built on May 2, 2019, 10:15 a.m.