Determinant Maximization with Linear Matrix Inequality Constraints
SIAM Journal on Matrix Analysis and Applications
Construction of marginally and conditionally restricted designs using multiplicative algorithms
Computational Statistics & Data Analysis
D-optimal design of a monitoring network for parameter estimation of distributed systems
Journal of Global Optimization
D-optimal designs via a cocktail algorithm
Statistics and Computing
Editorial: Special issue on algorithms for design of experiments
Computational Statistics & Data Analysis
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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.