Library of American University of Madaba
Your cart is empty.
Farebrother, Richard William.
L1-Norm and L∞-Norm Estimation An Introduction to the Least Absolute Residuals, the Minimax Absolute Residual and Related Fitting Procedures / [electronic resource] : by Richard William Farebrother. - VI, 58 p. online resource. - SpringerBriefs in Statistics, 2191-544X .
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.
9783642363009
Statistics.
Matrix theory.
Geometry.
Mechanics.
Mathematical statistics.
Statistics.
Statistical Theory and Methods.
Linear and Multilinear Algebras, Matrix Theory.
Geometry.
History of Mathematical Sciences.
Mechanics.
QA276-280
519.5
L1-Norm and L∞-Norm Estimation An Introduction to the Least Absolute Residuals, the Minimax Absolute Residual and Related Fitting Procedures / [electronic resource] : by Richard William Farebrother. - VI, 58 p. online resource. - SpringerBriefs in Statistics, 2191-544X .
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.
9783642363009
Statistics.
Matrix theory.
Geometry.
Mechanics.
Mathematical statistics.
Statistics.
Statistical Theory and Methods.
Linear and Multilinear Algebras, Matrix Theory.
Geometry.
History of Mathematical Sciences.
Mechanics.
QA276-280
519.5