A Simulated Annealing Algorithm for D‐Optimal Design for 2‐Way and 3‐Way Polynomial Regression with Correlated Observations

Chang Li and Daniel C. Coster

Journal of Applied Mathematics, 2014, vol. 2014, issue 1

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.

Date: 2014
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https://doi.org/10.1155/2014/746914

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2014:y:2014:i:1:n:746914

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