ForecastFramework: A Basis for Modular Model Creation

Create modular models. Quickly prototype models whose input includes (multiple) time series data. Create pieces of model use cases separately, and swap out particular models as desired. Create modeling competitions, data processing pipelines, and re-useable models.

Version: 0.10.2
Depends: R6
Imports: abind, lubridate, dplyr, reshape2, magrittr, tibble
Suggests: testthat, knitr, rmarkdown, DAAG
Enhances: surveillance
Published: 2019-11-03
Author: Joshua Kaminsky [aut, cre], Justin Lessler [aut], Nicholas Reich [aut]
Maintainer: Joshua Kaminsky <jkaminsky at jhu.edu>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ForecastFramework results

Downloads:

Reference manual: ForecastFramework.pdf
Vignettes: DataPolymorphism
Forecasting
Prediction
Package source: ForecastFramework_0.10.2.tar.gz
Windows binaries: r-devel: ForecastFramework_0.10.2.zip, r-devel-gcc8: ForecastFramework_0.10.2.zip, r-release: ForecastFramework_0.10.2.zip, r-oldrel: ForecastFramework_0.10.2.zip
OS X binaries: r-release: ForecastFramework_0.10.2.tgz, r-oldrel: ForecastFramework_0.10.2.tgz
Old sources: ForecastFramework archive

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