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Activity Number:
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10
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Type:
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Invited
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Date/Time:
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Sunday, August 2, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #302976 |
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Title:
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Nonparametric Estimation and Survey Design for Preference Data
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Author(s):
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Guy Lebanon*+
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Companies:
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Georgia Institute of Technology
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Address:
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, Atlanta, GA, 30306,
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Keywords:
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Abstract:
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Statistical models on full and partial rankings of n items are often of limited practical use for large n due to computational consideration. We explore the use of nonparametric models for partially ranked data and derive computationally efficient procedures for their use for large n. The derivations are largely possible through combinatorial and algebraic manipulations based on the lattice of partial rankings. A bias-variance analysis and an experimental study demonstrate the applicability of the proposed method. We conclude with an application of the statistical analysis to the survey design problem in the context of preference data.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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