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

Record type: Article

We consider the problem of finding D-optimal designs for estimating the coefficients in a weighted polynomial regression model with a certain efficiency function depending on two unknown parameters, which models the 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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Citation

Biedermann, Stefanie and Dette, Holger (2003) A note on maximin and Bayesian D-optimal designs in weighted polynomial regression Mathematical Methods of Statistics, 12, (3), pp. 358-370.

More information

Published date: 2003
Keywords: maximin optimality, bayesian optimal designs, efficiency function, parameter estimation, Jacobi polynomials
Organisations: Statistics

Identifiers

Local EPrints ID: 41835
URI: http://eprints.soton.ac.uk/id/eprint/41835
PURE UUID: 1052fe98-e24e-484c-ab08-f3d57fe079c1

Catalogue record

Date deposited: 10 Oct 2006
Last modified: 17 Jul 2017 15:27

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Contributors

Author: Holger Dette

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