DESCRIPTION

Package: autoMrP
Type: Package
Title: Improving MrP with Ensemble Learning
Version: 1.1.0
Authors@R: c(
  person(
		given = "Reto",
		family = "Wüest",
		role = c("aut"),
		email = "wuest.reto@gmail.com",
		comment = c(ORCID = "0000-0002-7502-6489")),
  person(
		given = "Lucas",
	  family = "Leemann",
		role = c("aut"),
		email = "leemann@ipz.uzh.ch",
		comment = c(ORCID = "0000-0001-5201-869X")),
	person(
		given = "Florian",
	  family = "Schaffner",
		role = c("aut"),
		email = " schaffner@ipz.uzh.ch",
		comment = c(ORCID = "0000-0003-3352-6191")),
	person(
		given = "Philipp",
	  family = "Broniecki",
		role = c("aut", "cre"),
		email = "philippbroniecki@gmail.com",
		comment = c(ORCID = "0000-0001-9214-4404")),
	person(
		given = "Hadley",
		family = "Wickham",
		role = "ctb",
		email = "hadley@rstudio.com"))
Description: 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>.
URL: https://github.com/retowuest/autoMrP
BugReports: https://github.com/retowuest/autoMrP/issues
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),
	R.rsp (>= 0.46.0), nloptr (>= 2.1.1), quadprog (>= 1.5-8), cli (>= 3.6.3)
Suggests: R.rsp
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
VignetteBuilder: R.rsp