Package: SAEforest
Title: Mixed Effect Random Forests for Small Area Estimation
Version: 1.0.0
Authors@R: person("Patrick", "Krennmair", email = "patrick.krennmair@fu-berlin.de", role = c("aut", "cre"))
Description: Mixed Effects Random Forests (MERFs) are a data-driven,
    nonparametric alternative to current methods of Small Area Estimation
    (SAE). 'SAEforest' provides functions for the estimation of regionally
    disaggregated linear and nonlinear indicators using survey sample
    data. Included procedures facilitate the estimation of domain-level
    economic and inequality metrics and assess associated uncertainty.
    Emphasis lies on straightforward interpretation and visualization of results.
    From a methodological perspective, the package builds on approaches discussed in 
    Krennmair and Schmid (2022) <arXiv:2201.10933v2> and Krennmair 
    et al. (2022) <arXiv:2204.10736>.
License: GPL (>= 2)
URL: https://github.com/krennpa/SAEforest,
        https://krennpa.github.io/SAEforest/
Depends: R (>= 4.1.0)
Imports: caret, dplyr, ggplot2, haven, ineq, lme4, maptools, pbapply,
        pdp, ranger, reshape2, stats, vip
Suggests: R.rsp, sp, rgeos, testthat (>= 3.0.0)
Encoding: UTF-8
RoxygenNote: 7.2.1
LazyData: true
VignetteBuilder: R.rsp
NeedsCompilation: no
Config/testthat/edition: 3
Packaged: 2022-09-06 11:37:18 UTC; Patrick
Author: Patrick Krennmair [aut, cre]
Maintainer: Patrick Krennmair <patrick.krennmair@fu-berlin.de>
Repository: CRAN
Date/Publication: 2022-09-07 17:50:06 UTC
Built: R 4.1.1; ; 2022-09-14 00:50:08 UTC; unix
