R-optimal designs for poisson regression model in two parameters

Tofan Kumar Biswal

Author(s)

Tofan Kumar Biswal Department of Statistics, Central University of Odisha,Sunabeda 763004,India

Abstract

In the generalized linear model (GLM) setup, the information matrix depends on the unknown parameters of the model. In such a situation, an experimenter has to adopt the approach of finding local optimal designs i.e. first guess the best value for the parameters and then calculate the optimal designs [see Chernoff (1953)]. In this paper, locally R-optimal designs for the Poisson regression model with two parameters including intercept are discussed. The R-optimality criterion has been proposed in the literature as an alternative to the most frequently used D-optimality criterion when the experimenter wishes to minimize the volume of the confidence region for unknown parameters based on Bonferroni t-intervals [see Dette (1997)]. The necessary and sufficient conditions of this optimality criterion are confirmed through the equivalence theorem.

Publication Details

Page(s) 285-300

DOI DOI not available

Published Journal: Pakistan Journal of Statistics, Volume: 40, Issue: 3, Year: 2024

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Keywords

Poisson regression model, Information matrix, Equivalence theorem., R-optimal design, Bonferroni t-intervals

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