A Framework for Producing Small Area Estimates Based on Area-Level Models in R

被引:0
作者
Harmening, Sylvia [1 ]
Kreutzmann, Ann-Kristin [1 ]
Schmidt, Soeren [1 ]
Salvati, Nicola [2 ]
Schmid, Timo [3 ]
机构
[1] Free Univ Berlin, Sch Business & Econ, Inst Stat & Econometr, Garystr 21, D-14195 Berlin, Germany
[2] Univ Pisa, Dept Econ & Management, Via C Ridolfi 10, I-56124 Pisa, Italy
[3] Otto Friedrich Univ Bamberg, Inst Stat, Feldkirchenstr 21, D-96052 Bamberg, Germany
关键词
MEAN-SQUARED ERROR; FAY-HERRIOT MODEL; INDICATORS; PACKAGE; INFORMATION; PREDICTORS;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The R package emdi facilitates the estimation of regionally disaggregated indicators using small area estimation methods and provides tools for model building, diagnostics, presenting, and exporting the results. The package version 1.1.7 includes unit-level small area models that rely on access to micro data. The area-level model by Fay and Herriot (1979) and various extensions have been added to the package since the release of version 2.0.0. These extensions include (a) area-level models with back-transformations, (b) spatial and robust extensions, (c) adjusted variance estimation methods, and (d) area-level models that account for measurement errors. Corresponding mean squared error estimators are implemented for assessing the uncertainty. User-friendly tools like a stepwise variable selection, model diagnostics, benchmarking options, high quality maps and results exportation options enable a complete analysis procedure. The functionality of the package is illustrated by examples based on synthetic data for Austrian districts.
引用
收藏
页码:316 / 341
页数:26
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