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

Documentation:

Reference manual:

dbnlearn.html , dbnlearn.pdf

Downloads:

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

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