Dynamic regression for time series using Extreme Gradient Boosting with hyper-parameter tuning via Bayesian Optimization.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.6) |
| Imports: | rBayesianOptimization, xgboost, purrr, abind, ggplot2, readr, stringr, lubridate, narray, fANCOVA, imputeTS, scales, tictoc, bizdays |
| Published: | 2021-04-28 |
| Author: | Giancarlo Vercellino |
| Maintainer: | Giancarlo Vercellino <giancarlo.vercellino at gmail.com> |
| License: | GPL-3 |
| URL: | <https://github.com/dmlc/xgboost>, <https://github.com/yanyachen/rBayesianOptimization> |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | audrex results |
| Reference manual: | audrex.pdf |
| Package source: | audrex_1.0.0.tar.gz |
| Windows binaries: | r-devel: audrex_1.0.0.zip, r-release: audrex_1.0.0.zip, r-oldrel: audrex_1.0.0.zip |
| macOS binaries: | r-release (arm64): audrex_1.0.0.tgz, r-release (x86_64): audrex_1.0.0.tgz, r-oldrel: audrex_1.0.0.tgz |
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