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Optimal designs for the prediction of individual parameters in hierarchical models
Author(s) -
Prus Maryna,
Schwabe Rainer
Publication year - 2016
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/rssb.12105
Subject(s) - computer science , optimal design , multilevel model , hierarchical database model , linear model , mathematics , machine learning , data mining
Summary Characterizations of optimal designs are derived for the prediction of individual response curves within the framework of hierarchical linear mixed models. It is shown that the so‐obtained optimal designs may differ substantially from those propagated in the literature so far and that the latter may become useless in terms of their performance.

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