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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>.
Getting started
Browse package contents
Package details |
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| Author | Robson Fernandes [aut, cre, cph] |
| Maintainer | Robson Fernandes <robson.fernandes@usp.br> |
| License | MIT + file LICENSE |
| Version | 0.1.0 |
| Package repository | View on CRAN |
| Installation |
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