OOS: Out-of-Sample Time Series Forecasting (original) (raw)
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 |
| 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 |
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