A Text Book on the Method of Least Squares
Author: Mansfield Merriman
Publisher:
Published: 1884
Total Pages: 214
ISBN-13:
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Data Analysis Using the Method of Least Squares
Author: John Wolberg
Publisher: Springer Science & Business Media
Published: 2006-02-08
Total Pages: 257
ISBN-13: 3540317201
DOWNLOAD EBOOKDevelops the full power of the least-squares method Enables engineers and scientists to apply the method to their specific problem Deals with linear as well as with non-linear least-squares, parametric as well as non-parametric methods
Solving Least Squares Problems
Author: Charles L. Lawson
Publisher: SIAM
Published: 1995-12-01
Total Pages: 348
ISBN-13: 0898713560
DOWNLOAD EBOOKThis 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.
A Text-book on the Method of Least Squares ...
Author: Mansfield Merriman
Publisher:
Published: 1924
Total Pages:
ISBN-13:
DOWNLOAD EBOOKIntroduction to Applied Linear Algebra
Author: Stephen Boyd
Publisher: Cambridge University Press
Published: 2018-06-07
Total Pages: 477
ISBN-13: 1316518965
DOWNLOAD EBOOKA groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
A Text Book on the Method of Least Squares
Author: Mansfield Merriman
Publisher:
Published: 1893
Total Pages: 218
ISBN-13:
DOWNLOAD EBOOKThe Total Least Squares Problem
Author: Sabine Van Huffel
Publisher: SIAM
Published: 1991-01-01
Total Pages: 302
ISBN-13: 0898712750
DOWNLOAD EBOOKThis 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.
The Least-Squares Finite Element Method
Author: Bo-nan Jiang
Publisher: Springer Science & Business Media
Published: 1998-06-22
Total Pages: 444
ISBN-13: 9783540639343
DOWNLOAD EBOOKThis is the first monograph on the subject, providing a comprehensive introduction to the LSFEM method for numerical solution of PDEs. LSFEM is simple, efficient and robust, and can solve a wide range of problems in fluid dynamics and electromagnetics.
Regression Analysis
Author: Ashish Sen
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 361
ISBN-13: 1461244706
DOWNLOAD EBOOKAn up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis, and thus ideally suited for those interested in the theory as well as those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines, showing the difficulties typically encountered in the practice of regression analysis. Consequently, this book provides a sound foundation in the theory of this important subject.
Linear Models and Generalizations
Author: C. Radhakrishna Rao
Publisher: Springer Science & Business Media
Published: 2007-10-15
Total Pages: 583
ISBN-13: 3540742271
DOWNLOAD EBOOKRevised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights of coverage include sensitivity analysis and model selection, an analysis of incomplete data, an analysis of categorical data based on a unified presentation of generalized linear models, and an extensive appendix on matrix theory.
