L [1] -Norm and L [∞] -Norm estimation : an introduction to the least absolute residuals, the minimax absolute residual and related fitting procedures
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Bibliographic Information
L [1] -Norm and L [∞] -Norm estimation : an introduction to the least absolute residuals, the minimax absolute residual and related fitting procedures
（Springer Briefs in statistics）
Springer, c2013
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Note
On t.p. "[1]" and "[∞]" is subscript
Includes bibliographical references and index
Description and Table of Contents
Description
This monograph is concerned with the fitting of linear relationships in the context of the linear statistical model. As alternatives to the familiar least squared residuals procedure, it investigates the relationships between the least absolute residuals, the minimax absolute residual and the least median of squared residuals procedures. It is intended for graduate students and research workers in statistics with some command of matrix analysis and linear programming techniques.
Table of Contents
Introduction.- Point Fitting Problems in One- and Two-dimensions.- The Hyperplane Fitting Problem in Two or More Dimensions.- Linear Programming Computations.- Statistical Theory.- The Least Median of Squared Residuals Procedure.- Mechanical Representations.- References.- Index of Names.
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