Modelling Multivariate Binary Data with Blocks of Specific OneFactor 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 


Author  Matthieu Marbac and Mohammed Sedki 
Maintainer  Mohammed Sedki <mohammed.sedki@upsud.fr> 
License  GPL (>= 2) 
Version  1.1 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.