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2014 A Simulated Annealing Algorithm for D-Optimal Design for 2-Way and 3-Way Polynomial Regression with Correlated Observations
Chang Li, Daniel C. Coster
J. Appl. Math. 2014: 1-6 (2014). DOI: 10.1155/2014/746914

Abstract

Much of the previous work in D-optimal design for regression models with correlated errors focused on polynomial models with a single predictor variable, in large part because of the intractability of an analytic solution. In this paper, we present a modified, improved simulated annealing algorithm, providing practical approaches to specifications of the annealing cooling parameters, thresholds, and search neighborhoods for the perturbation scheme, which finds approximate D-optimal designs for 2-way and 3-way polynomial regression for a variety of specific correlation structures with a given correlation coefficient. Results in each correlated-errors case are compared with traditional simulated annealing algorithm, that is, the SA algorithm without our improvement. Our improved simulated annealing results had generally higher D-efficiency than traditional simulated annealing algorithm, especially when the correlation parameter was well away from 0.

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Chang Li. Daniel C. Coster. "A Simulated Annealing Algorithm for D-Optimal Design for 2-Way and 3-Way Polynomial Regression with Correlated Observations." J. Appl. Math. 2014 1 - 6, 2014. https://doi.org/10.1155/2014/746914

Information

Published: 2014
First available in Project Euclid: 2 March 2015

Digital Object Identifier: 10.1155/2014/746914

Rights: Copyright © 2014 Hindawi

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