Bayesian and maximin optimal designs for heteroscedastic regression models - Holger Dette; Linda M. Haines; Lorens A. Imhof (Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, 2003)
The problem of constructing standardized maximin D-optimal designs for weighted polynomial regression models is addressed. In particular it is shown that, by following the broad approach to the construction of maximin designs introduced recently by Dette, Haines and Imhof (2003), such designs can be obtained as weak limits of the corresponding Bayesian Φq-optimal designs. The approach is illustrated for two specific weighted polynomial models and also for a particular growth model.
Keywords: 519; Regression; Modell-Spezifikation; Theorie; Heteroskedastizität