Simulation Tools for Small Area Estimation: Introducing the R-package saeSim

  • Sebastian Warnholz Sebastian Warnholz Department of Economics Freie Universität Berlin D-14195 Berlin
  • Timo Schmid Timo Schmid Department of Economics Freie Universität Berlin D-14195 Berlin

Abstract

The demand for reliable regional estimates from sample surveys has been substantially grown over the last decades. Small area estimation provides statistical methods to produce reliable predictions when the sample sizes in regions are too small to apply direct estimators. Model- and design-based simulations are used to gain insights into the quality of the introduced methods. In this article we present a framework which may help to guarantee the reproducibility of simulation studies in articles and during research. The introduced R-package saeSim is adjusted to provide a simulation environment for the special case of small area estimation. The package may allow the prospective researcher during the research process to produce simulation studies with a minimal eort of coding.
Published
2016-02-29
How to Cite
Warnholz, S., & Schmid, T. (2016). Simulation Tools for Small Area Estimation: Introducing the R-package saeSim. Austrian Journal of Statistics, 45(1), 55-69. https://doi.org/10.17713/ajs.v45i1.89
Section
Special Issue on R