Ebook: Nonlinear Lp-Norm Estimation

Complete with valuable FORTRAN programs that help solve nondifferentiable nonlinear Lp and Linf-norm estimation problems, this important reference/text extensively delineates ahistory of Lp-norm estimation. It examines the nonlinear Lp-norm estimation problem that is a viable alternative to least squares estimation problems where the underlying error distribution is nonnormal, i.e., non-Gaussian. "Nonlinear Lp-Norm Estimation" addresses both computational and statistical aspects of Lp-norm estimation problems to bridge the gap between these two fields ... contains 70 useful illustrations ... discusses linear Lp-norm as well as nonlinear L1, Linf, and Lp-norm estimation problems ... provides all appropriate computational algorithms and FORTRAN listings for nonlinear Lp and Linf-norm estimation problems ... guides readers with clear end of-chapter notes on related topics and outstanding research publications ... contains numerical examples plus several practical problems ... and shows how the data can prescribe various applications of Lp-norm alternatives. "Nonlinear Lp-Norm Estimation" is an indispensable reference for statisticians, operations researchers, numerical analysts, applied mathematicians, biometricians, and computer scientists, as well as a text for graduate students in statistics or computer science.