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Estimation of random regression parameters
Author(s) -
Wimmer G.
Publication year - 1980
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.4710220206
Subject(s) - mathematics , statistics , linear regression , uniqueness , estimation , regression , value (mathematics) , regression analysis , unbiased estimation , best linear unbiased prediction , computer science , mathematical analysis , artificial intelligence , selection (genetic algorithm) , management , economics , estimator
The problem of the best linear unbiased estimation (BLUE) of random regression parameters is considered. It is proved that increasing informations about the mean value of the parameters both extend the class of estimable linear functionals and improve on the estimation. In all investigated cases the uniqueness of BLUE is proved. In the case of known mean values the BLUE is shown to be numerically equivalent with the MMSEE almost everywhere. A numerical example shows the improvements of BLUE due to increasing informations about the mean values of the parameters.