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A Monte Carlo Study of Robustness of Preliminary Test Estimators in Pooling Means

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A Monte Carlo Study of Robustness of Preliminary Test Estimators in Pooling Means

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dc.contributor.author Han, Chien-Pai en
dc.contributor.author Bancroft, T. A. en
dc.date.accessioned 2010-06-03T17:54:27Z en
dc.date.available 2010-06-03T17:54:27Z en
dc.date.issued 1982-12 en
dc.identifier.uri http://hdl.handle.net/10106/2314 en
dc.description.abstract Pooling data, when justified, for estimating the target mean is advantageous when the sample size is small from the target population. In case it is doubtful whether two sets of data have the same mean, a normal test or a t test can be used for testing the equality of the two means depending on variance known or unknown. A preliminary test estimator is then constructed for estimating the population mean. We study the robustness of the preliminary test estimators when certain populations are not normal. The result of a Monte Carlo study is given, when the populations are either uniform or exponential. The relative efficiencies of the preliminary test estimators are studied. It is found that the preliminary test estimators are quite robust. en
dc.language.iso en_US en
dc.publisher University of Texas at Arlington en
dc.relation.ispartofseries Technical Report;194 en
dc.subject Normal test en
dc.subject T test en
dc.subject Preliminary test estimator en
dc.subject Populations size en
dc.subject.lcsh Monte Carlo method en
dc.subject.lcsh Mathematics Research en
dc.title A Monte Carlo Study of Robustness of Preliminary Test Estimators in Pooling Means en
dc.type Technical Report en
dc.publisher.department Department of Mathematics en

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