Overview
- Single source of information about this important area of research
- Wide-ranging discussion of least absolute residuals, minimax residual and least median of squared residuals fitting procedures
- Several new results not previously published in book form
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
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Table of contents (7 chapters)
Keywords
About this book
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.
Authors and Affiliations
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Bibliographic Information
Book Title: L1-Norm and L∞-Norm Estimation
Book Subtitle: An Introduction to the Least Absolute Residuals, the Minimax Absolute Residual and Related Fitting Procedures
Authors: Richard William Farebrother
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-3-642-36300-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2013
Softcover ISBN: 978-3-642-36299-6Published: 16 April 2013
eBook ISBN: 978-3-642-36300-9Published: 03 April 2013
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: VI, 58
Topics: Statistical Theory and Methods, Linear and Multilinear Algebras, Matrix Theory, Geometry, History of Mathematical Sciences, Classical Mechanics