Article ID Journal Published Year Pages File Type
417615 Computational Statistics & Data Analysis 2012 9 Pages PDF
Abstract

We prove that the standard nonparametric mean estimator for judgment post-stratification is inadmissible under squared error loss within a certain class of linear estimators. We derive alternate estimators that are admissible in this class, and we show that one of them is always better than the standard estimator. The reduction in mean squared error from using this alternate estimator can be as large as 10% for small set sizes and small sample sizes.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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