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Semi-bayesian D-optimal designs and estimation procedures for mean and variance functions.

By Martina Vandebroek and Peter Goos

Abstract

Semi-Bayesian D-optimal designs for fitting mean and variance functions are derived for some prior distributions on the variance function parameters. The impact of the mean of the prior and of the uncertainty about this mean is analyzed. Simulation studies are performed to investigate whether the choice of design has a substantial impact on the efficiency of the mean and the variance function parameter estimation and whether the D-optimality criterion is appropriate irrespective of the method applied to estimate the variance function parameters.Functions;

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