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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 Farebrother



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Autore: Farebrother Richard Visualizza persona
Titolo: 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 Farebrother Visualizza cluster
Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013
Edizione: 1st ed. 2013.
Descrizione fisica: 1 online resource (58 p.)
Disciplina: 519.5
519.5/44
Soggetto topico: Statistics 
Matrix theory
Algebra
Geometry
Mathematics
History
Mechanics
Statistical Theory and Methods
Linear and Multilinear Algebras, Matrix Theory
History of Mathematical Sciences
Classical Mechanics
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: 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.  .
Sommario/riassunto: 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.
Titolo autorizzato: L1-Norm and L∞-Norm Estimation  Visualizza cluster
ISBN: 3-642-36300-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910437861403321
Lo trovi qui: Univ. Federico II
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Serie: SpringerBriefs in Statistics, . 2191-544X