This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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632
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #306461 |
Title:
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Parametric vs. Nonparametric Approach for Interval Estimators of Multivariate Ranking Parameters
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Author(s):
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Livio Corain*+ and Rosa Arboretti
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Companies:
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University of Padova and University of Padova
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Address:
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, Vicenza, 36100, Italy
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Keywords:
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multivariate ranking ;
pairwise comparisons ;
nonparametric combination
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Abstract:
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The purpose of this work is to present and to critically compare some novel parametric and nonparametric interval estimation procedures for the problem of ranking several multivariate populations. Depending on the assumptions made about the random errors, the distribution of ranking parameter estimators can be derived in a parametric or nonparametric way. However, as demonstrated by a simulation study and by an application to a complex real case study, the parametric approach presents a number of drawbacks and limitations. Conversely, thanks to its robustness and flexibility, the permutation approach appears to be more reliable and powerful. These findings are not only of theoretical interest but also have a practical relevance, especially to industrial research where a reliable global ranking in terms of performance of all investigated products/prototypes is a very natural goal.
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