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)” forthcoming in 'Journal of Politics'. Final pre-print version: <>.

Version: 0.98
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)
Suggests: rmarkdown, R.rsp
Published: 2021-01-21
Author: Reto Wüest ORCID iD [aut], Lucas Leemann ORCID iD [aut], Philipp Broniecki ORCID iD [aut, cre], Hadley Wickham [ctb]
Maintainer: Philipp Broniecki <philippbroniecki at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: autoMrP results


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


Package source: autoMrP_0.98.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): autoMrP_0.98.tgz, r-release (x86_64): autoMrP_0.98.tgz, r-oldrel: autoMrP_0.98.tgz


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