audrex: Automatic Dynamic Regression using Extreme Gradient Boosting

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

Downloads:

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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