Improvd downward branch and bound algorithm for regression variable selection

Subset (feature) selection for least squares regression is a common problem, which is combinartorial, hence is computationally NP hard. This code provides a tool using the improved downward branch and bound approach to solve this problem efficiently. One of the applications of this algorithm is to select globally optimal controlled variables for self-optimizing control.