【摘 要】
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Diaconis and Sturmfels (1998) developed an algorithm for sampling from conditional distributions for a statistical model of discrete exponential families,ba
【机 构】
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DepartmentofTechnologyManagementforInnovation,UniversityofTokyo
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Diaconis and Sturmfels (1998) developed an algorithm for sampling from conditional distributions for a statistical model of discrete exponential families,based on the algebraic theory of toric ideals.This algorithm is applied to exact tests of goodness-of-fit of statistical models for categorical data analysis through the notion of Markov bases.However,often Markov bases are large and difficult to compute.One reason for the difficulty is that Markov bases guarantee connectivity of all fibers.With a given particular data set,on the other hand,we are naturally interested in the connectivity of a particular fiber.However obtaining a subset of a Markov basis for connecting a particular fiber is also a difficult problem in general (e.g.Chen et al.(2008),Aoki and Takemura (2005)).
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