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D-optimal Factorial Designs under Generalized Linear Models
Communications in statistics. Simulation and computation (Commun. Stat. - Simul. Comput.), 2013
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. Recently Yang, Mandal and Majumdar (2013) considered full factorial and fractional factorial locally D-optimal designs for binary response and two-level experimental factors. In this paper, we extend their results to a general setup with response belonging to a single-parameter exponential family and for multi-level predictors.
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