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Sinopsis
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 a great number of areas in sciences 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 Problem was the leading reference on least squares problems for many years. The updated second edition stands out compared to other books on the topic 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;
- covers generalized, constrained, and nonlinear least squares problems as well as partial least squares and regularization methods for discrete ill-posed problems; and
- contains a bibliography with more than 1100 historical and recent references, providing a unique survey of past and present research in the field.
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Acerca del autor
Åke Björck is a professor emeritus at Linköping University, Sweden. He is the author of many research papers and books on numerical analysis and matrix computations. He served as managing editor of the journal BIT Numerical Mathematics from 1993 to 2003 and he is a Fellow of SIAM.
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Numerical Methods for Least Squares Problem
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SIAM - Society for Industrial and Applied Mathematics, 2024
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ISBN 13: 9781611977943
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Numerical Methods for Least Squares Problems
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Numerical Methods For Least Squares Problem
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Numerical Methods For Least Squares Problem
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ISBN 13: 9781611977943
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Numerical Methods for Least Squares Problem
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SIAM - Society for Industrial and Applied Mathematics, 2024
ISBN 10: 1611977940
ISBN 13: 9781611977943
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Numerical Methods For Least Squares Problem
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ISBN 10: 1611977940
ISBN 13: 9781611977943
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Numerical Methods for Least Squares Problems
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ISBN 13: 9781611977943
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Paperback. Condición: New. Second Edition. 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 a great number of areas in sciences 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 Problem was the leading reference on least squares problems for many years. The updated second edition stands out compared to other books on the topic 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;covers generalized, constrained, and nonlinear least squares problems as well as partial least squares and regularization methods for discrete ill-posed problems; andcontains a bibliography with more than 1100 historical and recent references, providing a unique survey of past and present research in the field. Nº de ref. del artículo: LU-9781611977943
Cantidad disponible: 3 disponibles
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Numerical Methods For Least Squares Problem
Publicado por
SIAM - Society for Industrial and Applied Mathematics, 2024
ISBN 10: 1611977940
ISBN 13: 9781611977943
Nuevo
Tapa blanda
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 47979181-n
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Numerical Methods for Least Squares Problems
Publicado por
Society for Industrial and Applied Mathematics,U.S., US, 2024
ISBN 10: 1611977940
ISBN 13: 9781611977943
Nuevo
Paperback
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. Second Edition. 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 a great number of areas in sciences 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 Problem was the leading reference on least squares problems for many years. The updated second edition stands out compared to other books on the topic 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;covers generalized, constrained, and nonlinear least squares problems as well as partial least squares and regularization methods for discrete ill-posed problems; andcontains a bibliography with more than 1100 historical and recent references, providing a unique survey of past and present research in the field. Nº de ref. del artículo: LU-9781611977943
Cantidad disponible: 3 disponibles