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OOS: Out-of-Sample Time Series Forecasting

A comprehensive and cohesive API for the out-of-sample forecasting workflow: data preparation, forecasting - including both traditional econometric time series models and modern machine learning techniques - forecast combination, model and error analysis, and forecast visualization.

Version: 1.0.0
Depends: R (≥ 4.0.0)
Imports: caret, dplyr, forecast, furrr, future, ggplot2, glmnet, imputeTS, lmtest, lubridate, magrittr, purrr, sandwich, stats, tidyr, vars, xts, zoo
Suggests: knitr, testthat, rmarkdown, quantmod
Published: 2021-03-17
DOI: 10.32614/CRAN.package.OOS
Author: Tyler J. Pike [aut, cre]
Maintainer: Tyler J. Pike <tjpike7 at gmail.com>
BugReports: https://github.com/tylerJPike/OOS/issues
License: GPL-3
URL: https://github.com/tylerJPike/OOS, https://tylerjpike.github.io/OOS/
NeedsCompilation: no
CRAN checks: OOS results

Documentation:

Reference manual: OOS.pdf
Vignettes: Window functions

Downloads:

Package source: OOS_1.0.0.tar.gz
Windows binaries: r-devel: OOS_1.0.0.zip, r-release: OOS_1.0.0.zip, r-oldrel: OOS_1.0.0.zip
macOS binaries: r-release (arm64): OOS_1.0.0.tgz, r-oldrel (arm64): OOS_1.0.0.tgz, r-release (x86_64): OOS_1.0.0.tgz, r-oldrel (x86_64): OOS_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=OOS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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