1. Asymptotic normality of least-square estimators in multivariate singular linear models
- Author
-
Wolfgang H. Schmidt
- Subjects
Multivariate statistics ,Control and Optimization ,Local asymptotic normality ,Applied Mathematics ,Linear model ,Asymptotic distribution ,Estimator ,Extension (predicate logic) ,Management Science and Operations Research ,Asymptotic theory (statistics) ,Statistics ,Applied mathematics ,Central limit theorem ,Mathematics - Abstract
An extension of a central limit theorem of F. EICKER for linear vector forms is used to derive conditions for the asymptotic normality of Least-Square Estimators in multivariate linear singular models with stochastically independent error terms. These conditions are shown to be necessary too in some cases. Several previous results concerning asymptotic normality of Least-Square Estimators in regular models are special cases of the theory developed in this paper.
- Published
- 1975
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