dbnlearn: Dynamic Bayesian Network Structure Learning, Parameter Learning and Forecasting

It allows to learn the structure of univariate time series, learning parameters and forecasting. Implements a model of Dynamic Bayesian Networks with temporal windows, with collections of linear regressors for Gaussian nodes, based on the introductory texts of Korb and Nicholson (2010) <doi:10.1201/b10391> and Nagarajan, Scutari and Lèbre (2013) <doi:10.1007/978-1-4614-6446-4>.

Version: 0.1.0
Depends: R (≥ 3.4)
Imports: bnlearn, bnviewer, ggplot2
Published: 2020-07-30
DOI: 10.32614/CRAN.package.dbnlearn
Author: Robson Fernandes [aut, cre, cph]
Maintainer: Robson Fernandes <robson.fernandes at usp.br>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: dbnlearn results


Reference manual: dbnlearn.pdf


Package source: dbnlearn_0.1.0.tar.gz
Windows binaries: r-devel: dbnlearn_0.1.0.zip, r-release: dbnlearn_0.1.0.zip, r-oldrel: dbnlearn_0.1.0.zip
macOS binaries: r-release (arm64): dbnlearn_0.1.0.tgz, r-oldrel (arm64): dbnlearn_0.1.0.tgz, r-release (x86_64): dbnlearn_0.1.0.tgz, r-oldrel (x86_64): dbnlearn_0.1.0.tgz


Please use the canonical form https://CRAN.R-project.org/package=dbnlearn to link to this page.