Locally optimal designs for generalized linear models within the family of Kiefer $\Phi_k$-criteria

Abstract

Locally optimal designs for generalized linear models are derived at certain values of the regression parameters. In the present paper a general setup of the generalized linear model is considered. Analytic solutions for optimal designs are developed under Kiefer $\Phi_k$-criteria highlighting the D- and A-optimal designs. By means of The General Equivalence Theorem necessary and sufficient conditions in term of intensity values are obtained to characterize the locally optimal designs. In this context, linear predictors are assumed constituting first order models with and without intercept on appropriate experimental regions.