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...

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...