Abstract

We derive an explicit representation of the general non-i.i.d. error covariance matrix of the general linear model vector such that the likelihood ratio test statistic for testing certain linear restrictions on the parameter vector is robust against certain forms of dependency and heteroscedasticity.  In doing so, we correct two proposed explicit covariance matrix characterizations given in Khatri (1981).

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