품질경영학회지 (Journal of Korean Society for Quality Management)
- 제29권1호
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- Pages.11-23
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- 2001
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- 1229-1889(pISSN)
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- 2287-9005(eISSN)
Laplace-Metropolis알고리즘에 의한 다항로짓모형의 변수선택에 관한 연구
Laplace-Metropolis Algorithm for Variable Selection in Multinomial Logit Model
초록
This paper is concerned with suggesting a Bayesian method for variable selection in multinomial logit model. It is based upon an optimal rule suggested by use of Bayes rule which minimizes a risk induced by selecting the multinomial logit model. The rule is to find a subset of variables that maximizes the marginal likelihood of the model. We also propose a Laplace-Metropolis algorithm intended to suggest a simple method forestimating the marginal likelihood of the model. Based upon two examples, artificial data and empirical data examples, the Bayesian method is illustrated and its efficiency is examined.
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