In this note we consider the {\it general} linear regression model

This paper deals with the general partitioned linear regression model where the regressor matrix $X=\pmatrix{X_1 & X_2\cr}$ may be deficient in column rank, the dispersion matrix $V$ is possibly singular, $\beta^t=\pmatrix{\beta_1^t & \beta_2^t\cr}$ - being partitioned according to $X$ - is the...

In practice factorizations of a generalized inverse often arise from factorizations of the matrix which is to be inverted. In addition to full rank factorizations, normal factorizations and singular value decompositions (SVD) there are other factorizations of particular matrices that are natural...

This paper deals with the general possibly singular linear model. It is assumed that in addition to the sample information we have some nonstochastic prior information concerning the unknown regression coefficients that can be expressed in form of linear independent inequality constraints. Since...