時間：5月26日（周一）下午3：30至4：30
地點：研究生樓206
主講人：楊杰，美國伊利諾伊大學芝加哥分校的副教授
Title: D-optimal Factorial Designs under Generalized Linear Models
Abstract:
Generalized linear models (GLMs) have been used widely for modelling the mean response both for discrete and continuous random variables with an emphasis on categorical response.  We consider the problem of obtaining locally D-optimal designs for factorial experiments with response belonging to a single-parameter exponential family and multi-level predictors. We obtain a characterization for a design to be locally D-optimal. Based on this characterization, we develop efficient numerical techniques to search for locally D-optimal designs. Using prior distributions on the parameters, we investigate EW D-optimal designs, that are designs which maximize the determinant of the expected information matrix. It turns out that these designs are much easier to find and still highly efficient compared to Bayes D-optimal designs, as well as quite robust.
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