Package: MoTBFs
Type: Package
Title: Learning Hybrid Bayesian Networks using Mixtures of Truncated
        Basis Functions
Version: 1.0
Author: Inmaculada Pérez-Bernabé, Antonio Salmerón
Maintainer: Inmaculada Pérez-Bernabé <iperezbernabe@gmail.com>
Description: Learning, manipulation and  evaluation of mixtures of  truncated basis  functions 
  (MoTBFs),  which include mixtures of  polynomials (MOPs) and  mixtures of truncated 
  exponentials (MTEs). MoTBFs are a flexible framework for modelling hybrid Bayesian
  networks. The  package provides  functionality for learning  univariate, multivariate and
  conditional  densities, with the  possibility of incorporating prior  knowledge. Structural
  learning of hybrid Bayesian  networks is also provided. A set of useful tools is provided,
  including  plotting, printing  and likelihood  evaluation. This  package  makes use of  S3 
  objects, with two new classes called 'motbf' and 'jointmotbf'.
Depends: R (>= 3.2.0)
Imports: quadprog, lpSolve, bnlearn, methods
Suggests: mnormt
Encoding: UTF-8
License: LGPL-3
NeedsCompilation: yes
Repository: CRAN
Packaged: 2015-09-27 21:00:24 UTC; Inma
Date/Publication: 2015-09-28 09:26:43
