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

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 : Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Subject:	Regression \| Schätztheorie \| Theorie \| maximin optimality \| Bayesian optimal designs \| efficiency function \| parameter estimation \| Jacobi polynominals

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Series:	Technical Report ; 2003,03
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	817966579 [GVK] hdl:10419/49349 [Handle] RePEc:zbw:sfb475:200303 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010306264