Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Ann-Kristin Kreutzmann, Sören Pannier, Natalia Rojas-Perilla, Timo Schmid, Matthias Templ, Nikos Tzavidis
Title: The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators
Abstract: The R package emdi enables the estimation of regionally disaggregated indicators using small area estimation methods and includes tools for processing, assessing, and presenting the results. The mean of the target variable, the quantiles of its distribution, the headcount ratio, the poverty gap, the Gini coefficient, the quintile share ratio, and customized indicators are estimated using direct and model-based estimation with the empirical best predictor (Molina and Rao 2010). The user is assisted by automatic estimation of datadriven transformation parameters. Parametric and semi-parametric, wild bootstrap for mean squared error estimation are implemented with the latter offering protection against possible misspecification of the error distribution. Tools for (a) customized parallel computing, (b) model diagnostic analyses, (c) creating high quality maps and (d) exporting the results to Excel and OpenDocument Spreadsheets are included. The functionality of the package is illustrated with example data sets for estimating the Gini coefficient and median income for districts in Austria.

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Paper: The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators     Download PDF (Downloads: 670)
emdi_1.1.6.tar.gz: R source package Download (Downloads: 42; 1MB)
v91i07.R: R replication code Download (Downloads: 70; 5KB)

DOI: 10.18637/jss.v091.i07

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.