Numerical Methods for Least Squares Problems
Numerical Methods for Least Squares Problems

Author: Ake Bjorck

Publisher: SIAM

Published: 1996-01-01

Total Pages: 425

ISBN-13: 9781611971484

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The method of least squares was discovered by Gauss in 1795. It has since become the principal tool to reduce the influence of errors when fitting models to given observations. Today, applications of least squares arise in a great number of scientific areas, such as statistics, geodetics, signal processing, and control. In the last 20 years there has been a great increase in the capacity for automatic data capturing and computing. Least squares problems of large size are now routinely solved. Tremendous progress has been made in numerical methods for least squares problems, in particular for generalized and modified least squares problems and direct and iterative methods for sparse problems. Until now there has not been a monograph that covers the full spectrum of relevant problems and methods in least squares. This volume gives an in-depth treatment of topics such as methods for sparse least squares problems, iterative methods, modified least squares, weighted problems, and constrained and regularized problems. The more than 800 references provide a comprehensive survey of the available literature on the subject.

Solving Least Squares Problems
Solving Least Squares Problems

Author: Charles L. Lawson

Publisher: SIAM

Published: 1995-12-01

Total Pages: 348

ISBN-13: 0898713560

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This Classic edition includes a new appendix which summarizes the major developments since the book was originally published in 1974. The additions are organized in short sections associated with each chapter. An additional 230 references have been added, bringing the bibliography to over 400 entries. Appendix C has been edited to reflect changes in the associated software package and software distribution method.

Numerical Methods for Least Squares Problems, Second Edition
Numerical Methods for Least Squares Problems, Second Edition

Author: Åke Björck

Publisher: SIAM

Published: 2024-07-05

Total Pages: 509

ISBN-13: 1611977959

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The method of least squares, discovered by Gauss in 1795, is a principal tool for reducing the influence of errors when fitting a mathematical model to given observations. Applications arise in many areas of science and engineering. The increased use of automatic data capturing frequently leads to large-scale least squares problems. Such problems can be solved by using recent developments in preconditioned iterative methods and in sparse QR factorization. The first edition of Numerical Methods for Least Squares Problems was the leading reference on the topic for many years. The updated second edition stands out compared to other books on this subject because it provides an in-depth and up-to-date treatment of direct and iterative methods for solving different types of least squares problems and for computing the singular value decomposition. It also is unique because it covers generalized, constrained, and nonlinear least squares problems as well as partial least squares and regularization methods for discrete ill-posed problems. The bibliography of over 1,100 historical and recent references provides a comprehensive survey of past and present research in the field. This book will be of interest to graduate students and researchers in applied mathematics and to researchers working with numerical linear algebra applications.

The Total Least Squares Problem
The Total Least Squares Problem

Author: Sabine Van Huffel

Publisher: SIAM

Published: 1991-01-01

Total Pages: 302

ISBN-13: 0898712750

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This is the first book devoted entirely to total least squares. The authors give a unified presentation of the TLS problem. A description of its basic principles are given, the various algebraic, statistical and sensitivity properties of the problem are discussed, and generalizations are presented. Applications are surveyed to facilitate uses in an even wider range of applications. Whenever possible, comparison is made with the well-known least squares methods. A basic knowledge of numerical linear algebra, matrix computations, and some notion of elementary statistics is required of the reader; however, some background material is included to make the book reasonably self-contained.

Numerical Matrix Analysis
Numerical Matrix Analysis

Author: Ilse C. F. Ipsen

Publisher: SIAM

Published: 2009-07-23

Total Pages: 135

ISBN-13: 0898716764

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Matrix analysis presented in the context of numerical computation at a basic level.

Applied Numerical Linear Algebra
Applied Numerical Linear Algebra

Author: James W. Demmel

Publisher: SIAM

Published: 1997-08-01

Total Pages: 426

ISBN-13: 0898713897

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This comprehensive textbook is designed for first-year graduate students from a variety of engineering and scientific disciplines.

Least-Squares Finite Element Methods
Least-Squares Finite Element Methods

Author: Pavel B. Bochev

Publisher: Springer Science & Business Media

Published: 2009-04-28

Total Pages: 669

ISBN-13: 0387689222

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Since their emergence, finite element methods have taken a place as one of the most versatile and powerful methodologies for the approximate numerical solution of Partial Differential Equations. These methods are used in incompressible fluid flow, heat, transfer, and other problems. This book provides researchers and practitioners with a concise guide to the theory and practice of least-square finite element methods, their strengths and weaknesses, established successes, and open problems.

Numerical Matrix Analysis
Numerical Matrix Analysis

Author: Ilse C. F. Ipsen

Publisher: SIAM

Published: 2009-01-01

Total Pages: 136

ISBN-13: 089871768X

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The purpose of this book is to promote understanding of two phenomena: sensitivity of linear systems and least squares problems, and numerical stability of algorithms. Sensitivity and stability are analyzed as mathematical properties, without reference to finite precision arithmetic. The material is presented at a basic level, emphasizing ideas and intuition, but in a mathematically rigorous fashion. The derivations are simple and elegant, and the results are easy to understand and interpret. The book is self-contained. It was written for students in all areas of mathematics, engineering, and the computational sciences, but can easily be used for self-study. This text differs from other numerical linear algebra texts by offering the following: a systematic development of numerical conditioning; a simplified concept of numerical stability in exact arithmetic; simple derivations; a high-level view of algorithms; and results for complex matrices.