Representations of the covariance matrix for robustness in the gauss-markov model

Abstract

This paper considers some extensions of the results of Rao and Rao and Mitra. They gave a table of general representations of the covariance matrix in terms of the given design matrix, under which various statistical procedures in the least squares theory based on the simple Gauss-Markov model with the spherical covariance matrix are also valid under the general Gauss-Markov model. We shall give extended tables adding some more results relating to robustness, especially in connection with the estimation and testing of hypotheses on linear parametric functions

Keywords:

• Gauss-Markov model
• representation for robustness
• least squares theory
• linear hypotheses