The use of generalized inverses in restricted maximum likelihood

The calculus of generalized inverses and related concepts in matrix algebra is applied to the general restricted maximum likelihood problem. Some new results on g-inverses, Kronecker products, and matrix differentials are presented. For the restricted maximum likelihood problem we obtain generalizations of the well-known results of Aitchison and Silvey 1]. We use the approach recently developed by Heijmans and Magnus 13, 14] to allow for non-i.i.d. observations. A nonlinear seemingly unrelated regressions model with possibly singular covariance matrix and linear restrictions (NLSURSR) is analyzed, and the linear expenditure system (LES) is discussed as a special case.