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dbnlearn: Dynamic Bayesian Network Structure Learning, Parameter Learningand 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 + fileLICENSE
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

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=dbnlearnto link to this page.


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