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: 0.9.0
Depends: R6
Imports: abind, lubridate, dplyr, reshape2, magrittr
Suggests: testthat, ggplot2, knitr, rmarkdown, dtplyr, data.table, DAAG, R.utils
Published: 2017-06-28
Author: Joshua Kaminsky [aut, cre]
Maintainer: Joshua Kaminsky <jkaminsky at jhu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: ForecastFramework results

Downloads:

Reference manual: ForecastFramework.pdf
Vignettes: DataPolymorphism
Forecasting
Prediction
ClassDiagram
Package source: ForecastFramework_0.9.0.tar.gz
Windows binaries: r-devel: ForecastFramework_0.9.0.zip, r-release: ForecastFramework_0.9.0.zip, r-oldrel: ForecastFramework_0.9.0.zip
OS X binaries: r-release: ForecastFramework_0.9.0.tgz, r-oldrel: ForecastFramework_0.9.0.tgz

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