Computationally efficient parallel algorithms for downdating the least-squares estimator of the ordinary linear model (OLM) are proposed. The algorithms are block versions of sequential Givens strategies and efficiently exploit the triangular structure of the matrices. The first strategy...

A computationally efficient branch-and-bound strategy for finding the subsets of the most statistically significant variables of a vector autoregressive (VAR) model from a given search subspace is proposed. Specifically, the candidate submodels are obtained by deleting columns from the...

Efficient algorithms for diagnosing influential data points are investigated. Techniques examining potentially influential subsets are considered. Given a list of candidate observations, a new row-dropping algorithm (RDA) computes all possible observation-subset regression models. It employs a...

The General Linear Model (GLM) is the parent model of econometrics. Simultaneous equations and seemingly unrelated regression equation (SURE) models, to name but a few, can be formulated as a GLM. The estimation of the GLM can be viewed as a Generalized Linear Least-Squares problem (GLLSP). The...

In simultaneous equation models (SEMs) the assumption that the covariance matrix of the disturbances is non-singular cannot always be made. For example, allocation models and models with precise observations which may imply linear constraints on the parameters, have singular disturbance...

The main computational tool for solving SUR or simultaneous equations models is the generalized QR decomposition (GQRD) of an exogenous matrix A and the Cholesky factorization of a dispersion matrix C. Initially the GQRD computes the QRD of A and then the RQD of QC, where Q is an orthogonal...

Vector Autoregressive processes of order p (VAR(p)) with coefficient restrictions can be formulated as a SURE model. The response vectors and the coefficient matrices of the regression equations comprise columns from a Toeplitz matrix. Numerical and computational methods that solve the SURE...