Bayesian D‐optimal designs for error‐in‐variables models

• Published in: Applied stochastic models in business and industry Vol. 33; no. 3; pp. 269 - 281
• Main Authors: Konstantinou, Maria, Dette, Holger
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01.05.2017
• Subjects: Bayesian analysis; Bayesian optimal designs; classical errors; Design parameters; D‐optimality; Economic models; error‐in‐variables models; Least squares method; Maximum likelihood estimation; Optimality criteria; Optimization; Regression analysis; Robust design

Bayesian optimality criteria provide a robust design strategy to parameter misspecification. We develop an approximate design theory for Bayesian D‐optimality for nonlinear regression models with covariates subject to measurement errors. Both maximum likelihood and least squares estimation are studi...