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Minimum Norm Invariant Quadratic Estimation of a Covariance Matrix in Linear Model
Author(s) -
Chaubey Yogendra P.
Publication year - 1982
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710240508
Subject(s) - mathematics , covariance , estimation of covariance matrices , covariance matrix , quadratic equation , norm (philosophy) , statistics , quadratic model , linear model , intraclass correlation , general linear model , law of total covariance , covariance intersection , geometry , response surface methodology , political science , law , psychometrics
A general linear model with a known covariance structure is considered. The method of Minimum Norm Quadratic estimation extending R AO'S (1972) argument is outlined. This method is illustrated for a particular model where it is noted that MINQE used for estimating intraclass correlation coefficient yields the maximum likelihood estimate.