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 |
| 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:
Downloads:
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