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 |
| 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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