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An efficient branch-and-bound algorithm for computing the best-subset regression models is proposed. The algorithm avoids the computation of the whole regression tree that generates all possible subset models. It is formally shown that if the branch-and-bound test holds, then the current subtree together with its right-hand side subtrees are cut. This(More)
A regression graph to enumerate and evaluate all possible subset regression models is introduced. The graph is a generalization of a regression tree. All the spanning trees of the graph are minimum spanning trees and provide an optimal computational procedure for generating all possible submodels. Each minimum spanning tree has a different structure and(More)
and its staff, in particular to the head of department Peter Kropf, for hosting me. Abstract Computationally intensive algorithms for model selection and robust regression are considered. Particular emphasis is put on regression trees. The QR decomposition is the main computational tool to solve the linear models. Givens rotations are employed to compute(More)
The journal of Computational Statistics and Data Analysis (CSDA) regularly publishes papers with a strong algorithmic and software component. Some recent CSDA related articles can be found in This is the first CSDA special issue on Statistical Algorithms and Software. It brings together a number of contributions that relate to statistical software,(More)