L1-Norm and L∞-Norm Estimation [electronic resource] : An Introduction to the Least Absolute Residuals, the Minimax Absolute Residual and Related Fitting Procedures / by Richard William Farebrother.

By: Farebrother, Richard William [author.]
Contributor(s): SpringerLink (Online service)
Material type: TextTextSeries: SpringerBriefs in Statistics: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: VI, 58 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642363009Subject(s): Statistics | Matrix theory | Algebra | Geometry | Mathematics | History | Mechanics | Statistics | Statistical Theory and Methods | Linear and Multilinear Algebras, Matrix Theory | Geometry | History of Mathematical Sciences | MechanicsAdditional physical formats: Printed edition:: No titleDDC classification: 519.5 LOC classification: QA276-280Online resources: Click here to access online
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.  .
In: Springer eBooksSummary: 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.
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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.  .

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.

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