Local computations of the iterative proportional scaling procedure for hierarchical models

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• 作者：Ping-Feng Xu ; Jubo Sun ; Na Shan ; ^{dann831@gmail.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Hierarchical models ; Iterative proportional scaling ; Simulated annealing
• 刊名：Computational Statistics & Data Analysis
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：95
• 期：Complete
• 页码：17-23
• 全文大小：406 K

文摘

The maximum likelihood estimation of hierarchical models for contingency tables is often carried out by the iterative proportional scaling (IPS) procedure. In this paper, we propose local computations of the IPS procedure by partitioning generators. The proposed implementation, called IPSP for short, first partitions generators into several non-overlapping and non-empty blocks, and then adjusts marginal counts in each block locally. To find an approximation to the optimal partition resulting the least complexity, we apply the simulated annealing algorithm. Moreover, local computations can speed up the implementation of the IPS procedure using junction trees. Numerical experiments are presented to illustrate the efficiency of local computations.