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 teh GMT holds is derived.Second, we establish a nonlinear version of the maximal GMT and describe some...

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...

In a general normal regression model, this paper first derives the LUB(least upper bound)for the covariance matrix of a GLSE relative to the applied to the (unrestricted) Zellner estimator in the N-equation SUR model and to the GLSE in a heteroscedastic model.