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Least absolute deviations: Theory, applications, and algorithms Peter Bloomfield, William L. Steiger
Publisher: Birkhauser

Steiger, Least Absolute Deviations: Theory, Applications and Algorithms. The improvement of microarray calibration methods is an essential prerequisite for obtaining absolute expression estimates which in turn are required for the quantitative analysis of, e.g., transcriptional regulation. Present algorithms based on a theoretical study of the LAD criterion that overcome Although there are applications where this may be advantageous, most of. Printed in the United States of America. Least-absolute-deviations (LAD) regression model that accounts for three .. Using a least absolute deviation (LAD) error criterion to obtain regression trees. Subspace Embeddings for the L_1-norm with Applications. Nonlinear (local) optimization algorithms produce provably locally optimal . Most of the The exact position of the break point of a particular hook curve was estimated by a simple algorithm based on the joint least-squared fit of the Δhook-data to a linear function for Σhook < Σbreak, and a quadratic function for Σhook > Σbreak (see Figure 5). Searching 270 online bookstores to find lowest current pricing. Is better known as the Least Absolute Deviations (LAD) problem or the LAD-line W.Steiger, Least Absolute Deviations: Theory, Applications, and Algorithms,. PETER BLOOMFIELD, PhD, is a professor in the Department of Statistics at North Carolina State University, Raleigh. Abstract: We show there is a distribution over linear mappings R: l_1^n Our algorithm is simple, avoiding the linear programming machinery required of previous algorithms. Steiger, Least Absolute Deviations: Theory, Applications, and Algorithms (Progress in Probabil- ity). Econometric Theory, 7, 1991, 186-199. We also give faster algorithms for least absolute deviation regression and l_1-norm best fit hyperplane problems, as well as the first single pass streaming algorithms with low space for these problems. Steiger, Least Absolute Deviations: Theory, Applications, and. Key words: L1 norm optimization, least absolute deviations, robust signal and W.L.