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Activity Number:
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586
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 6, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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International Chinese Statistical Association
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| Abstract - #303638 |
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Title:
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Parametic Inference in Ranked Set Sampling Based on a Missing Data Model
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Author(s):
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Omer Ozturk*+
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Companies:
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The Ohio State University
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Address:
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404 Cockins Hall, 1958 Neil Avenue, Columbus, OH, 43210,
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Keywords:
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Mixture model ; EM-algorithm ; Judgment ranking ; Fisher Information ; Order statistics ; Missing observation
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Abstract:
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Ranked set sampling procedure generates independent judgment order statistics from a population of interest. Distributional properties of these order statistics depend on the quality of ranking information. Ranking information can be modeled in different ways. In this talk, we use Bohn-Wolfe (Bohn and Wolfe, 1994, JASA) model to look at distributional properties of judgment order statistics. It is shown that Bohn-Wolfe model can be derived from a missing data model with a particular missing data mechanism. The properties of this missing data model is investigated, distributional properties of judgment order statistics are developed and the parameters of this model are estimated.
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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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