Package: MoTBFs
Type: Package
Title: Learning Hybrid Bayesian Networks using Mixtures of Truncated
Basis Functions
Version: 1.4.1
Author: Inmaculada Pérez-Bernabé, Antonio Salmerón, Thomas D. Nielsen, Ana D. Maldonado
Maintainer: Ana D. Maldonado <ana.d.maldonado@ual.es>
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 (I. Pérez-Bernabé, A. Salmerón, H. Langseth (2015) <doi:10.1007/978-3-319-20807-7_36>; H. Langseth, T.D. Nielsen, I. Pérez-Bernabé, A. Salmerón (2014) <doi:10.1016/j.ijar.2013.09.012>; I. Pérez-Bernabé, A. Fernández, R. Rumí, A. Salmerón (2016) <doi:10.1007/s10618-015-0429-7>). 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, ggm, Matrix
Encoding: UTF-8
License: LGPL-3
NeedsCompilation: yes
Repository: CRAN
Packaged: 2022-04-18 13:15:36 UTC; amaldonado
Date/Publication: 2022-04-18 16:34:30 UTC
RoxygenNote: 7.1.2

Package: MoTBFs
Type: Package
Title: Learning Hybrid Bayesian Networks using Mixtures of Truncated
Basis Functions
Version: 1.4
Author: Inmaculada Pérez-Bernabé, Antonio Salmerón, Thomas D. Nielsen, Ana D. Maldonado
Maintainer: Ana D. Maldonado <ana.d.maldonado@ual.es>
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 (I. Pérez-Bernabé, A. Salmerón, H. Langseth (2015) <doi:10.1007/978-3-319-20807-7_36>; H. Langseth, T.D. Nielsen, I. Pérez-Bernabé, A. Salmerón (2014) <doi:10.1016/j.ijar.2013.09.012>; I. Pérez-Bernabé, A. Fernández, R. Rumí, A. Salmerón (2016) <doi:10.1007/s10618-015-0429-7>). 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, ggm, Matrix
Encoding: UTF-8
License: LGPL-3
NeedsCompilation: yes
Repository: CRAN
Packaged: 2020-06-19 14:38:02 UTC; anamaldonado
Date/Publication: 2020-06-19 15:20:02 UTC
RoxygenNote: 7.1.0