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Abstract Details
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Activity Number:
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525
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #300842 |
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Title:
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Improved Nonparametric Mean and Variance Estimators for Judgment Post-Stratification
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Author(s):
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Jesse Frey*+ and Timothy Feeman
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Companies:
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Villanova University and Villanova University
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Address:
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800 Lancaster Ave, Villanova, PA, 19085,
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Keywords:
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Judgment post-stratification ;
Ranked-set sampling ;
Admissibility ;
Variance estimation
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Abstract:
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We consider nonparametric estimation of the population mean and population variance using judgment post-stratification (JPS). We prove that the standard nonparametric JPS mean estimator is inadmissible under squared error loss within a certain class of linear estimators. We then derive alternate mean estimators that are admissible in this class, and we show that one of them is always better than the standard estimator. We also derive a new nonparametric JPS variance estimator that seems to outperform the JPS analogue of a well-known nonparametric variance estimator for ranked-set sampling.
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