Dynamic regression for time series using Extreme Gradient Boosting with hyper-parameter tuning via Bayesian Optimization or Random Search.
| Version: | 2.0.1 |
| Depends: | R (≥ 4.1) |
| Imports: | rBayesianOptimization (≥ 1.2.0), xgboost (≥ 1.4.1.1), purrr (≥ 0.3.4), ggplot2 (≥ 3.3.5), readr (≥ 2.1.2), stringr (≥ 1.4.0), lubridate (≥ 1.7.10), narray (≥ 0.4.1.1), fANCOVA (≥ 0.6-1), imputeTS (≥ 3.2), scales (≥ 1.1.1), tictoc (≥ 1.0.1), modeest (≥ 2.4.0), moments (≥ 0.14), Metrics (≥ 0.1.4), parallel (≥ 4.1.1), utils (≥ 4.1.1), stats (≥ 4.1.1) |
| Published: | 2022-03-23 |
| DOI: | 10.32614/CRAN.package.audrex |
| Author: | Giancarlo Vercellino |
| Maintainer: | Giancarlo Vercellino <giancarlo.vercellino at gmail.com> |
| License: | GPL-3 |
| URL: | https://rpubs.com/giancarlo_vercellino/audrex |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | audrex results |
| Reference manual: | audrex.pdf |
| Package source: | audrex_2.0.1.tar.gz |
| Windows binaries: | r-devel: audrex_2.0.1.zip, r-release: audrex_2.0.1.zip, r-oldrel: audrex_2.0.1.zip |
| macOS binaries: | r-release (arm64): audrex_2.0.1.tgz, r-oldrel (arm64): audrex_2.0.1.tgz, r-release (x86_64): audrex_2.0.1.tgz, r-oldrel (x86_64): audrex_2.0.1.tgz |
| Old sources: | audrex archive |
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