EconStor >
Technische Universität Dortmund >
Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen, Technische Universität Dortmund >
Technical Reports, SFB 475: Komplexitätsreduktion in multivariaten Datenstrukturen, TU Dortmund >

Please use this identifier to cite or link to this item:
Title:A note on maximin and Bayesian D-optimal designs in weighted polynomial regression PDF Logo
Authors:Biedermann, Stefanie
Dette, Holger
Issue Date:2003
Series/Report no.:Technical Report // Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2003,03
Abstract: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.
Subjects:maximin optimality
Bayesian optimal designs
efficiency function
parameter estimation
Jacobi polynominals
Document Type:Working Paper
Appears in Collections:Technical Reports, SFB 475: Komplexitätsreduktion in multivariaten Datenstrukturen, TU Dortmund

Files in This Item:
File Description SizeFormat
36985974X.pdf224.38 kBAdobe PDF
36985974X.psOriginal Publication216.66 kBPostscript
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.