print.SAEforest

Basic information of an <code>SAEforestObject</code> is printed.

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

print.SAEforest function

<dl><dt>x</dt>
<dd>Object of class <code>SAEforest</code>, representing point and MSE
estimates obtained by function <code>SAEforest_model</code>.</dd>
<dt>...</dt>
<dd>Optional additional inputs that are ignored for this method.</dd></dl>

Arguments

Prints a 'SAEforest' object — print.SAEforest

<dl>

<dt>x</dt>
<dd>Object of class <code>SAEforest</code>, representing point and MSE
estimates obtained by function <code>SAEforest_model</code>.</dd>


<dt>...</dt>
<dd>Optional additional inputs that are ignored for this method.</dd>

</dl>

print.SAEforest: Prints a 'SAEforest' object

Description

Usage

Value

Arguments

See Also