コバヤシ ゲンヤ
KOBAYASHI GENYA
小林 弦矢 所属 明治大学 商学部 職種 専任教授 |
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言語種別 | 英語 |
発行・発表の年月 | 2014/12 |
形態種別 | 学術雑誌 |
査読 | 査読あり |
標題 | A transdimensional approximate Bayesian computation using the pseudo-marginal approach for model choice |
執筆形態 | 単著 |
掲載誌名 | COMPUTATIONAL STATISTICS & DATA ANALYSIS |
掲載区分 | 国外 |
出版社・発行元 | ELSEVIER SCIENCE BV |
巻・号・頁 | 80,pp.167-183 |
著者・共著者 | Genya Kobayashi |
概要 | When the likelihood functions are either unavailable analytically or are computationally cumbersome to evaluate, it is impossible to implement conventional Bayesian model Choice methods. Instead, approximate Bayesian computation (ABC) or the likelihood-free method can be used in order to avoid direct evaluation of the intractable likelihoods. This paper proposes a new Markov chain Monte Carlo (MCMC) method for model choice. This method is based on the pseudo-marginal approach and is appropriate for situations where the likelihood functions for the competing models are intractable. This method proposes jumps between the models with different dimensionalities without matching the dimensionalities. Therefore, it enables the construction of a flexible proposal distribution. The proposal distribution used in this paper is convenient to implement and works well in the context of ABC. |
DOI | 10.1016/j.csda.2014.06.025 |
ISSN | 0167-9473 |