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Locally D-optimal designs for heteroscedastic polynomial measurement error models

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Locally D-optimal designs for heteroscedastic polynomial measurement error models

10$

Min-Jue Zhang & Rong-Xian Yue

Abstract

This paper considers constructions of optimal designs for heteroscedastic polynomial measurement error models. Corresponding approximate design theory is developed by using corrected score function approach, which leads to non-concave optimisation problems. For the weighted polynomial measurement error model of degree p with some commonly used heteroscedastic structures, the upper bounds for the number of support points of locally D-optimal designs can be determined explicitly. A numerical example is given to show how heteroscedastic structures affect the optimal designs.

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Year 2020
Language English
Format PDF
DOI 10.1007/s00184-019-00745-2