Extended Information Matrices for Optimal Designs when the Observations are Correlated II

Pazman, Andrej and Müller, Werner (1996) Extended Information Matrices for Optimal Designs when the Observations are Correlated II. Forschungsberichte / Institut für Statistik, 41. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.

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Abstract

Regression models with correlated errors lead to nonadditivity of the information matrix. This makes the usual approach of design optimization (approximation with a continuous design, application of an equivalence theorem, numerical calculations by a gradient algorithm) impossible. A method is presented that allows the construction of a gradient algorithm by altering the information matrices through adding of supplementary noise. A heuristic is formulated to circumvent the nonconvexity problem and the method is applied to typical examples from the literature. (author's abstract)

Item Type: Paper
Keywords: optimum design / correlated errors / extended information matrices / gradient algorithm
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 11 Jul 2006 10:25
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/1720

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