A maximal extension of the Gauss-Markov theorem and its nonlinear version

JOURNAL OF MULTIVARIATE ANALYSIS

卷:83

Article

Kariya, T ; Kurata, H

关键词: Gauss-Markov theorem;    nonlinear versions of Gauss-Markov theorem;    location-equivariant estimator;    generalized least squares estimator;    elliptically symmetric distribution;   

DOI  :  10.1006/jmva.2001.2050

来源: Elsevier

【 摘 要 】

In this paper, first we make a maximal extension of the well-known Gauss-Markov Theorem (GMT) in its linear framework. In particular, the maximal class of distributions of error term for which the GMT holds is derived. Second, we establish a nonlinear version of the maximal GMT and describe some interesting families of distributions of error term for which the nonlinear GMT holds. (C) 2002 Elsevier Science (USA).

【 授权许可】

Free