Abstract
We show, in the context of linear regression models, how D-optimal designs can be constructed in a sequential manner in order to address the joint problem of model discrimination and parameter estimation. A specific example is used to illustrate the proposed approach. The resulting design is compared to several existing designs based on the standard relative efficiency and the so-called expected relative efficiency.
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© 1998 Springer-Verlag Berlin Heidelberg
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Montepiedra, G., Yeh, A.B. (1998). Two-Stage Designs for Model Discrimination and Parameter Estimation. In: Atkinson, A.C., Pronzato, L., Wynn, H.P. (eds) MODA 5 — Advances in Model-Oriented Data Analysis and Experimental Design. Contributions to Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-58988-1_21
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DOI: https://doi.org/10.1007/978-3-642-58988-1_21
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1111-7
Online ISBN: 978-3-642-58988-1
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