Computing efficient exact designs of experiments using integer quadratic programming

Radoslav Harman and Lenka Filová

Computational Statistics & Data Analysis, 2014, vol. 71, issue C, 1159-1167

Abstract: A new method for computing exact experimental designs for linear regression models by integer quadratic programming is proposed. The key idea is to use the criterion of DQ-optimality, which is a quadratic approximation of the criterion of D-optimality in the neighbourhood of the approximate D-optimal information matrix. Several numerical examples are used to demonstrate that the D-efficiency of exact DQ-optimal designs is usually very high. An important advantage of this method is that it can be applied to situations with general linear constraints on permissible designs, including marginal and cost constraints.

Keywords: D-optimal design; DQ-optimal design; Exact design; Marginal constraints; Cost constraints; Integer quadratic programming (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:71:y:2014:i:c:p:1159-1167

DOI: 10.1016/j.csda.2013.02.021

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