This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 339
Type: Topic Contributed
Date/Time: Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #306701
Title: Constrained Nonparametric Estimation Using Ranked-Set Sampling with a Covariate
Author(s): Jesse Frey*+
Companies: Villanova University
Address: , Villanova, PA, 19085,
Keywords: Concomitant ; Convexity ; Judgment post-stratification ; Maximum likelihood estimation ; Stratified sampling ; Woodruff confidence intervals

Ranked-set sampling and judgment post-stratification are related schemes in which more efficient statistical inference is obtained by creating a stratification based on ranking information. The rankings that are used may be completely subjective, or they may be based on values of a covariate. Recent work has shown that regardless of how the rankings are done, the in-stratum cumulative distribution functions (CDFs) must satisfy certain constraints, and these constraints may be used to obtain better estimates of the in-stratum CDFs, the overall CDF, and the population mean. We show here that if the rankings are done according to a covariate, then tighter constraints must hold. We also show that under a mild stochastic ordering assumption, still tighter constraints must hold. Taking advantage of these new constraints leads to improved estimation of key population parameters.

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