A note on maximin and Bayesian D-optimal designs in weighted polynomial regression

Stefanie Biedermann; Holger Dette

We consider the problem of finding D-optimal designs for estimating the coefficients in a weighted polynominal regression model with a certain efficiency function depending on two unknown parameters, which models he heteroscedastic error structure. This problem is tackled by adopting a Bayesian and a maximin approach, and optimal designs supported on a minimal number of support points are determined explicitly.

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Year of publication:	2003
Authors:	Biedermann, Stefanie ; Dette, Holger
Publisher:	Dortmund : Univ., SFB 475
Subject:	maximin optimality \| Bayesian optimal designs \| efficiency function \| parameter estimation \| Jacobi polynominals \| Schätztheorie \| Estimation theory \| Regressionsanalyse \| Regression analysis \| Bayes-Statistik \| Bayesian inference