Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition (Statistics for Social Science and Behavioral Sciences)

More specially, it shows that projection matrices (projectors) and g-inverse matrices can be defined in various ways so that a vector space is decomposed into a direct-sum of (disjoint) subspaces.