Package: dbnlearn 0.1.0

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>.

Authors:Robson Fernandes [aut, cre, cph]

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Peer review:

Bug tracker:https://github.com/robson-fernandes/dbnlearn/issues

On CRAN:

bayesian-inferencebayesian-networksdynamic-bayesian-networksprobabilistic-graphical-modelstime-series

4 exports 12 stars 1.59 score 109 dependencies 26 scripts 248 downloads

Last updated 4 years agofrom:85b4c06549. Checks:OK: 1 ERROR: 6. Indexed: yes.

Exports:dbn.fitdbn.learndbn.predictdbn.preprocessing

Dependencies:assertthatbase64encbnlearnbnviewerbslibcachemcaretclasscliclockcodetoolscolorspacecommonmarkcpp11crayondata.tablediagramdigestdplyre1071evaluatefansifarverfastmapfontawesomeforeachfsfuturefuture.applygenericsggplot2globalsgluegowergtablehardhathighrhtmltoolshtmlwidgetshttpuvigraphipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmemoisemgcvmimeModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrpromisesproxypurrrR6rappdirsRColorBrewerRcpprecipesreshape2rlangrmarkdownrpartsassscalesshapeshinysourcetoolsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetinytextzdbutf8vctrsviridisLitevisNetworkwithrxfunxtableyaml