Special Colloquia, Department of Statistics Monday, February 26, 2001 4:30 PM in REC 113 Dr. Raquel Prado Universidad Simon Bolivar, Venezuela will speak on Bayesian Time-Varying Autoregressions: Models and Applications Abstract Time-varying autoregressive (TVAR) models have proven useful in describing the behavior of long time series that experience changes in quasi-periodic content over time. Beginning with the class of TVAR models in a Bayesian dynamic linear modeling framework, we review methodological aspects of time-domain decompositions that provide inferences on the structure underlying non-stationary time series. Recent model extensions that deal with model order order uncertainty, and are enabled using Markov Chain Monte Carlo simulation methods, are discussed. We emphasize the relevance of TVAR modeling in the context of biomedical signal processing, in particular, we consider analyses of multiple electroencephalographic (EEG) traces that arise in various neurophysiological settings. We conclude with comments about current research on multivariate autoregressive models. Refreshments will be available in MATH Library at 4:15 p.m.

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