Numerical solution of optimal allocation problems in stratified sampling under box constraints

Ralf Münnich (), Ekkehard Sachs () and Matthias Wagner ()

AStA Advances in Statistical Analysis, 2012, vol. 96, issue 3, 435-450

Abstract: Modern sampling designs in survey statistics, in general, are constructed in order to optimize the accuracy of estimators such as totals, means and proportions. In stratified random sampling a variance minimal solution was introduced by Neyman and Tschuprov. However, practical constraints may lead to limitations of the domain of sampling fractions which have to be considered within the optimization process. Special attention on the complexity of numerical solutions has to be paid in cases with many strata or when the optimal allocation has to be applied repeatedly, such as in iterative solutions of stratification problems. The present article gives an overview of recent numerical algorithms which allow adequate inclusion of box constraints in the numerical optimization process. These box constraints may play an important role in statistical modeling. Furthermore, a new approach through a fixed point iteration with a finite termination property is presented. Copyright Springer-Verlag 2012

Keywords: Optimal weights; Box constraints; Census 2011; Regula falsi; Fixed point iteration (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s10182-011-0176-z

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