A New Class of IMSE-Based Criteria for Optimal Designs in Multi-response Random Coefficient Regression Models
Lei He , Rong-Xian Yue
Communications in Mathematics and Statistics ›› : 1 -18.
A New Class of IMSE-Based Criteria for Optimal Designs in Multi-response Random Coefficient Regression Models
A new class of criteria for optimal designs in random coefficient regression (RCR) models with r responses is presented, which is based on the integrated mean squared error (IMSE) for the prediction of random effects. This class, referred to as
Optimal designs / Integrated mean squared error matrix / IMSE-optimality / Prediction / Mixed effects model
School of Mathematical Sciences, University of Science and Technology of China and Springer-Verlag GmbH Germany, part of Springer Nature
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