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:
Downloads:
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