Abstract
This paper considers the optimal design problem for predicting a linear combination of fixed and random effects when the variance components in the linear mixed model are known or unknown. New design criteria based on the mean squared error of the predictor are proposed to obtain the exact or continuous optimal designs. For unknown variance components, the uncertainty of their estimators is incorporated into the design criteria. Numerical results indicate the importance of this consideration. Special attention is paid to obtaining optimal designs for predicting individual curves or future observations.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
