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Abstract Details
Activity Number:
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656
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Marketing
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Abstract - #305695 |
Title:
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Bayesian Analysis on Unobserved Components
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Author(s):
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Woosuk Kim*+
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Companies:
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Address:
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8849 Harperpoint Dr, Cincinnati, OH, 45249, United States
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Keywords:
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MCMC ;
Discrete choice models ;
Bayesian
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Abstract:
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Different discrete choice models are derived under various specifications of the density of unobserved factor. We develop a discrete choice model under the assumption that the unobserved factors follow the multivariate skew normal distribution. Under the assumptions, we compute the choice probability of each category in the model. Because it is difficult to get a closed-form choice probability, we consider the Bayesian estimation using MCMC. Moreover, under the model assumptions, we explore whether or not the model can handle random taste variation, allows any pattern of substitution, and is applicable to panel data with temporally correlated errors.
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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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