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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 |
| 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 |
| Reference manual: | OOS.pdf |
| Vignettes: |
Window functions |
| 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 |
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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