autoMrP: Improving MrP with Ensemble Learning

A tool that improves the prediction performance of multilevel regression with post-stratification (MrP) by combining a number of machine learning methods. For information on the method, please refer to Broniecki, Wüest, Leemann (2020) ”Improving Multilevel Regression with Post-Stratification Through Machine Learning (autoMrP)” in the 'Journal of Politics'. Final pre-print version: <https://lucasleemann.files.wordpress.com/2020/07/automrp-r2pa.pdf>.

Version:	1.0.6
Depends:	R (≥ 3.6)
Imports:	rlang (≥ 0.4.5), dplyr (≥ 1.0.2), lme4 (≥ 1.1), gbm (≥ 2.1.5), e1071 (≥ 1.7-3), tibble (≥ 3.0.1), glmmLasso (≥ 1.5.1), EBMAforecast (≥ 1.0.0), foreach (≥ 1.5.0), doParallel (≥ 1.0.15), doRNG (≥ 1.8.2), ggplot2 (≥ 3.3.2), knitr (≥ 1.29), tidyr (≥ 1.1.2), purrr (≥ 0.3.4), forcats (≥ 0.5.1), vglmer (≥ 1.0.3), stringr (≥ 1.5.0)
Suggests:	R.rsp
Published:	2024-01-30
DOI:	10.32614/CRAN.package.autoMrP
Author:	Reto Wüest [aut], Lucas Leemann [aut], Florian Schaffner [aut], Philipp Broniecki [aut, cre], Hadley Wickham [ctb]
Maintainer:	Philipp Broniecki <philippbroniecki at gmail.com>
BugReports:	https://github.com/retowuest/autoMrP/issues
License:	GPL-3
URL:	https://github.com/retowuest/autoMrP
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	autoMrP results

Documentation:

Reference manual:	autoMrP.html , autoMrP.pdf
Vignettes:	autoMrP: Multilevel Models and Post-Stratification (MrP) Combined with Machine Learning in R (source)

Downloads:

Package source:	autoMrP_1.0.6.tar.gz
Windows binaries:	r-devel: autoMrP_1.0.6.zip, r-release: autoMrP_1.0.6.zip, r-oldrel: autoMrP_1.0.6.zip
macOS binaries:	r-release (arm64): autoMrP_1.0.6.tgz, r-oldrel (arm64): autoMrP_1.0.6.tgz, r-release (x86_64): autoMrP_1.0.6.tgz, r-oldrel (x86_64): autoMrP_1.0.6.tgz
Old sources:	autoMrP archive

Linking:

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