Optimal Designs for Minimax-Criteria in Random Coefficient Regression Models
Statistics Theory
2018-11-09 v1 Statistics Theory
Abstract
We consider minimax-optimal designs for the prediction of individual parameters in random coefficient regression models. We focus on the minimax-criterion, which minimizes the "worst case" for the basic criterion with respect to the covariance matrix of random effects. We discuss particular models: linear and quadratic regression, in detail.
Cite
@article{arxiv.1811.03472,
title = {Optimal Designs for Minimax-Criteria in Random Coefficient Regression Models},
author = {Maryna Prus},
journal= {arXiv preprint arXiv:1811.03472},
year = {2018}
}