Abstract Details
Activity Number:
|
494
|
Type:
|
Topic Contributed
|
Date/Time:
|
Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Section on Statistics in Marketing
|
Abstract #311898
|
View Presentation
|
Title:
|
Generalized Isotonized Mean Estimators for Judgment Post-Stratification with Multiple Rankers
|
Author(s):
|
Min Chen*+ and Johan Lim and Xinlei Wang and Johan Lim
|
Companies:
|
University of Texas at Dallas and Seoul National University and Southern Methodist University and Seoul National University
|
Keywords:
|
best linear unbiased estimator ;
generalized isotonic regression ;
matrix partial order ;
simple stochastic order ;
ranked set sampling ;
raking
|
Abstract:
|
We propose a new set of mean estimators for judgement post-stratified data with multiple rankers. The new estimators take into account matrix partial ordering in cumulative distribution functions of rank strata, and they are derived by improving existing estimators through employing the order constraints and solving a generalized isotonic regression problem. Numerical studies show that the proposed isotonized mean estimators outperform the existing estimators. Finally, the proposed estimators are applied to estimating the average tree height using the tree data in Chen et al. (2006).
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.