SAEforest: Mixed Effect Random Forests for Small Area Estimation

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>.

Getting started

Package details

AuthorPatrick Krennmair [aut, cre]
MaintainerPatrick Krennmair <patrick.krennmair@fu-berlin.de>
LicenseGPL (>= 2)
Version1.0.0
URL https://github.com/krennpa/SAEforest https://krennpa.github.io/SAEforest/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("SAEforest")

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SAEforest documentation built on Sept. 8, 2022, 1:05 a.m.