popNsize

This data contains simulated population data based on aggregates from <code>eusilcA_pop</code>,
which is based on <code>eusilcP</code> from package simFrame.

datasets

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>.

Patrick Krennmair

SAEforest

Mixed Effect Random Forests for Small Area Estimation

popNsize function

A data frame with 94 Austrian districts and corresponding synthetic
population numbers:<dl>
<dt>district</dt>
<dd>character; districts (94 levels).</dd><dt>N_i</dt>
<dd>numeric; simulated population of district.</dd>
</dl>

Format

Demographic population-size data — popNsize

A data frame with 94 Austrian districts and corresponding synthetic
population numbers:<dl>
<dt>district</dt>
<dd>character; districts (94 levels).</dd>

<dt>N_i</dt>
<dd>numeric; simulated population of district.</dd>


</dl>

popNsize: Demographic population-size data

Description

Usage

Arguments

Format