L1-Norm and L∞-Norm Estimation
Subtitle: An Introduction to the Least Absolute Residuals, the Minimax Absolute Residual and Related Fitting Procedures
By: by Richard William Farebrother
Contributors: SpringerLink (Online service)
Series: SpringerBriefs in Statistics
Publisher: Springer Berlin Heidelberg; Imprint: Springer
Published: 2013
Place of publication: Berlin, Heidelberg
Language: eng
Format: [electronic resource] :
Number of pages: 58
ISBN-13: 9783642363009
Subjects: Mechanics; Matrix Theory Linear and Multilinear Algebras; History of Mathematical Sciences; Statistics; Geometry; Statistical Theory and Methods; Mathematical statistics; Matrix theory
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: title: Introduction; title: Point Fitting Problems in One- and Two-dimensions; title: The Hyperplane Fitting Problem in Two or More Dimensions; title: Linear Programming Computations; title: Statistical Theory; title: The Least Median of Squared Residuals Procedure; title: Mechanical Representations; title: References; title: Index of Names. ​  .