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.

Author
Matthieu Marbac and Mohammed Sedki
Date of publication
2016-07-21 07:31:15
Maintainer
Mohammed Sedki <mohammed.sedki@u-psud.fr>
License
GPL (>= 2)
Version
1.1

View on R-Forge

Man pages

ComputeEmpiricCramer
Computation of the Empiric Cramer'v.
ComputeMvBinaryCramer
Computation of the model Cramer'v.
MvBinaryEstim
Create an instance of the ['MvBinaryResult'] class
MvBinaryExample
Simulated binary data: MvBinaryExample
MvBinary-package
MvBinary a package for Multivariate Binary data
MvBinaryProbaPost
Computation of the model Cramer'v.
MvBinaryResult-class
Constructor of ['MvBinaryResult'] class
plants
Real binary data: Plants
print-methods
Summary function.
summary-methods
Summary function.

Files in this package

MvBinary/DESCRIPTION
MvBinary/NAMESPACE
MvBinary/R
MvBinary/R/Classes.R
MvBinary/R/Metropolis-Hastings.R
MvBinary/R/MvBinaryEstim.R
MvBinary/R/ProbaPost.R
MvBinary/R/Summary.R
MvBinary/R/Tools.R
MvBinary/R/XEM.R
MvBinary/data
MvBinary/data/MvBinaryExample.rda
MvBinary/data/plants.rda
MvBinary/man
MvBinary/man/ComputeEmpiricCramer.Rd
MvBinary/man/ComputeMvBinaryCramer.Rd
MvBinary/man/MvBinary-package.Rd
MvBinary/man/MvBinaryEstim.Rd
MvBinary/man/MvBinaryExample.Rd
MvBinary/man/MvBinaryProbaPost.Rd
MvBinary/man/MvBinaryResult-class.Rd
MvBinary/man/plants.Rd
MvBinary/man/print-methods.Rd
MvBinary/man/summary-methods.Rd