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Transcript
Department of Statistics STATISTICS COLLOQUIUM AKIMICHI TAKEMURA Department of Mathematical Informatics University of Tokyo Introduction to the Holonomic Gradient Method in Statistics MONDAY, October 22, 2012, at 4:00 PM 133 Eckhart Hall, 5734 S. University Avenue Refreshments following the seminar in Eckhart 110 ABSTRACT The holonomic gradient method introduced by Nakayama et al. (2011) presents a new methodology for evaluating normalizing constants of probability distributions and for obtaining the maximum likelihood estimate of a statistical model. The method utilizes partial differential equations satisfied by the normalizing constant and is based on the Grobner basis theory for the ring of differential operators. In this talk we give an introduction to this new methodology. The method has already proved to be useful for problems in directional statistics and in classical multivariate distribution theory involving hypergeometric functions of matrix arguments. For further information and inquiries about building access for persons with disabilities, please contact Dan Moreau at 773.702.8333 or send him an email at [email protected]. If you wish to subscribe to our email list, please visit the following website: https://lists.uchicago.edu/web/arc/statseminars.