Special Colloquia, Department of Statistics Friday, February 2, 2001 3:30 PM in MATH 215 Mr. Yuguo Chen Stanford University will speak on Conditional Inference on Zero-One Tables: A Sequential Importance Sampling Approach Abstract The Monte Carlo method of sequential importance sampling (SIS) has been shown to be a versatile and powerful tool for solving complex problems in dynamic systems. We describe a sequential importance sampling approach to making conditional inferences about zero-one tables, a problem which is not inherently dynamic. Our procedure compares favorably with Markov Chain Monte Carlo techniques. We apply our method to test ecological theories about competition between species in Darwin's finch data. We discuss the insights that our approach to this problem provides for developing an efficient SIS methodology. We briefly describe other general principles behind efficient SIS algorithms we have developed for inference on genealogical trees, permutation tests on truncated data and filtering and smoothing in hidden Markov models. Refreshments will be available in MATH Library at 4:15 p.m.

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