A note on maximin and Bayesian D-optimal designs in weighted polynomial regression
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), 358-370.
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Description/Abstract
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.
| Item Type: | Article |
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| Related URLs: | |
| Keywords: | maximin optimality, bayesian optimal designs, efficiency function, parameter estimation, Jacobi polynomials |
| Subjects: | Q Science > QA Mathematics H Social Sciences > HA Statistics |
| Divisions: | University Structure - Pre August 2011 > School of Mathematics > Statistics |
| Item ID: | 41835 |
| Date Deposited: | 10 Oct 2006 |
| Last Modified: | 28 Jun 2012 10:41 |
| Contributors: | Biedermann, Stefanie (Author) Dette, Holger (Author) |
| Date: | 2003 |
| Status: | Published |
| Contact Email Address: | s.biedermann@soton.ac.uk |
| URI: | http://eprints.soton.ac.uk/id/eprint/41835 |
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