Accession Number:

AD0647775

Title:

ON THE EXTENSION OF GAUSS-MARKOV THEOREM TO COMPLEX MULTIVARIATE LINEAR MODELS,

Descriptive Note:

Corporate Author:

NEBRASKA UNIV LINCOLN

Personal Author(s):

Report Date:

1966-09-01

Pagination or Media Count:

46.0

Abstract:

The purpose of the paper is to develop a distribution-free theory of linear estimation under various complex multivariate linear models, which are more general than the usual model to which the standard techniques of multivariate analysis of variance are applicable. In particular, necessary and sufficient conditions under which unique best linear unbiased estimates of linear functions of location parameters exist are obtained. The extension of the Gauss-Markov Theorem to the standard multivariate model was first made by the author in a previous work. In this paper, the further generalizations of these results to multiresponse designs where the standard model is inapplicable are considered. Author

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE