R-optimal designs for multi-response regression models with multi-factors

Pengqi Liu, Lucy L. Gao and Julie Zhou

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 2, 340-355

Abstract: We investigate R-optimal designs for multi-response regression models with multi-factors, where the random errors in these models are correlated. Several theoretical results are derived for R-optimal designs, including scale invariance, reflection symmetry, line and plane symmetry, and dependence on the covariance matrix of the errors. All the results can be applied to linear and non-linear models. In addition, an efficient algorithm based on an interior point method is developed for finding R-optimal designs on discrete design spaces. The algorithm is very flexible, and can be applied to any multi-response regression model.

Date: 2022
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DOI: 10.1080/03610926.2020.1748655

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