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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 |
| 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 |
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