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 <[email protected]> 
License  GPL (>= 2) 
Version  1.1 
Package repository  View on CRAN 
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