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 L├Ębre (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
Author: Robson Fernandes [aut, cre, cph]
Maintainer: Robson Fernandes <robson.fernandes at usp.br>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: dbnlearn results

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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: dbnlearn_0.1.0.tgz, r-oldrel: dbnlearn_0.1.0.tgz

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