On selection of statistics for approximate Bayesian computing (or the method of simulated moments)

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• 作者：Michael Creel^a ; ^{michael.creel@uab.es" class="auth_mail" title="E-mail the corresponding author} ; Dennis Kristensen^b ; ¹ ; ^{d.kristensen@ucl.ac.uk" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Approximate Bayesian computation ; Likelihood-free methods ; Selection of statistics ; Method of simulated moments
• 刊名：Computational Statistics & Data Analysis
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：100
• 期：Complete
• 页码：99-114
• 全文大小：444 K

文摘

A cross validation method for selection of statistics for Approximate Bayesian Computing, and for related estimation methods such as the Method of Simulated Moments, is presented. The method uses simulated annealing to minimize the cross validation criterion over a combinatorial search space that may contain an extremely large number of elements. A first simple example, for which optimal statistics are known from theory, shows that the method is able to select these optimal statistics out of a large set of candidate statistics. A second example of selection of statistics for a stochastic volatility model illustrates the method in a more complex case. Code to replicate the results, or to use the method for other applications, is provided at http://www.runmycode.org/companion/view/1116.