$V$-invariant methods, generalised least squares problems, and the Kalman filter

Abstract

V-invariant methods for the generalised least squares problem extend the techniques based on orthogonal factorization for ordinary least squares to problems with multiscaled, even singular covariances. These methods are summarised briefly here, and the ability to handle multiple scales indicated. An application to a class of Kalman filter problems derived from generalised smoothing splines is considered. Evidence of severe illconditioning of the covariance matrices is demonstrated in several examples. This suggests that this is an appropriate application for the V-invariant techniques.