Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/49363
Authors: 
Dette, Holger
Melas, Viatcheslav B.
Pepelyshev, Andrey
Year of Publication: 
2003
Series/Report no.: 
Technical Report // Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2003,37
Abstract: 
In this paper we investigate locally E- and c-optimal designs for exponential regression models of the form _k i=1 ai exp(??ix). We establish a numerical method for the construction of efficient and locally optimal designs, which is based on two results. First we consider the limit ?i ? ? and show that the optimal designs converge weakly to the optimal designs in a heteroscedastic polynomial regression model. It is then demonstrated that in this model the optimal designs can be easily determined by standard numerical software. Secondly, it is proved that the support points and weights of the locally optimal designs in the exponential regression model are analytic functions of the nonlinear parameters ?1, . . . , ?k. This result is used for the numerical calculation of the locally E-optimal designs by means of a Taylor expansion for any vector (?1, . . . , ?k). It is also demonstrated that in the models under consideration E-optimal designs are usually more efficient for estimating individual parameters than D-optimal designs.
Subjects: 
E-optimal design
c-optimal design
exponential models
locally optimal designs
Chebyshev systems
heteroscedastic polynomial regression
Document Type: 
Working Paper

Files in This Item:
File
Size
178.42 kB
497.26 kB





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