MoTBFs

Learning Hybrid Bayesian Networks using Mixtures of Truncated Basis Functions

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'.

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Description file content

Package
MoTBFs
Type
Package
Title
Learning Hybrid Bayesian Networks using Mixtures of Truncated Basis Functions
Version
1.2
Author
Inmaculada Pérez-Bernabé, Antonio Salmerón, Thomas D. Nielsen, Ana D. Maldonado
Maintainer
Ana D. Maldonado
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) ; H. Langseth, T.D. Nielsen, I. Pérez-Bernabé, A. Salmerón (2014) ; I. Pérez-Bernabé, A. Fernández, R. Rumí, A. Salmerón (2016) ). 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
Encoding
UTF-8
License
LGPL-3
NeedsCompilation
yes
Repository
CRAN
Packaged
2020-01-14 17:57:53 UTC; anamaldonado
Date/Publication
2020-01-14 19:00:02 UTC
RoxygenNote
6.1.99.9001

install.packages('MoTBFs')

1.2

10 days ago

Ana D. Maldonado

LGPL-3

Depends on

R (>= 3.2.0)

Imports

quadprog, lpSolve, bnlearn, methods, ggm

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