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audrex: Automatic Dynamic Regression using Extreme Gradient Boosting

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
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

Documentation:

Reference manual: audrex.pdf

Downloads:

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

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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