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
Institutions:	Institut für Wirtschafts- und Sozialstatistik, Universität Dortmund
Subject:	maximin optimality \| Bayesian optimal designs \| efficiency function \| parameter estimation \| Jacobi polynominals

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Extent:	application/pdf
Series:	Technical Reports.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 2003,03
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10009295173