Extended Information Matrices for Optimal Designs when the Observations are Correlated

Pazman, Andrej and Müller, Werner (1996) Extended Information Matrices for Optimal Designs when the Observations are Correlated. Forschungsberichte / Institut für Statistik, 53. 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 11:32
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/1416

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