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Linear Least Squares Computations

information becomes available and how to test linear hypotheses.Linear Least Squares Computations features many structured exercises that guidethe;

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Matrices, Moments and Quadrature with Applications

in iterative methods for solving linear systems and computing parameters in least squares and total least squares; and solving ill-posed problems using;

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Numerical Methods in Matrix Computations

for linear systems, least squares and eigenvalue problems. A thorough analysis of the stability, accuracy, and complexity of the treated;

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Least Squares Data Fitting with Applications

environmental sciences to geophysics. Anyone working with problems of linear and nonlinear least squares fitting will find this book invaluable as a;

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Quaternion Matrix Computations

quaternion linear systems, generalized least squares problems, and quaternion right eigenvalue problems. Formulas of the methods are derived, and;

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Elementary Linear Algebra

, covering many important real-world applications, including graph theory, circuit theory, Markov chains, elementary coding theory, least-squares;

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Data Fitting and Uncertainty

* fitting of linear and nonlinear functions with one- or multi-dimensional variables * weighted least-squares * outlier detection;

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Monte Carlo Library Least-Squares Approach to EDXRF Elemental Analysis

of all the elements to be analyzed plus any other required background libraries, which are then used in the linear library least-squares (LLS;

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Fitting Linear Relationships

statistical estimation procedures. Detailed descriptions of the fitting of linear relationships by the method of least squares and the closely related;

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Concise Introduction to Linear Algebra

, matrices quickly into more advanced topics including, LU decomposition, orthogonal decomposition, Least squares solutions, Gram-Schmidt process;

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Concise Introduction to Linear Algebra

, matrices quickly into more advanced topics including, LU decomposition, orthogonal decomposition, Least squares solutions, Gram-Schmidt process;

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New Perspectives in Partial Least Squares and Related Methods

New Perspectives in Partial Least Squares and Related Methods shares original, peer-reviewed research from presentations during the 2012;

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Statistical Methods for the Analysis of Biomedical Data

regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and;

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Sensitivity Analysis in Linear Regression

, which is not accounted for in a standard least squares estimate, but is important where regression coefficients are used to apportion effects;

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Supremum & Stability of Weighted Pseudoinverses & Weighted Least Squares Problems

of weighted pseudoinverses, weighted least squares problems and constrained weighted least squares problems, and stable methods for solving weighted;

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Computational Methods of Linear Algebra

This book presents methods for the computational solution of some important problems of linear algebra: linear systems, linear least;

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Computational Methods of Linear Algebra

This book presents methods for the computational solution of some important problems of linear algebra: linear systems, linear least;

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Methods And Applications Of Linear Models

: * Newly added topics including least squares, the cell means model, and graphical inspection of data in the AVE method * Frequent conceptual and;

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A Mathematical Primer for Social Statistics

and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares;

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Partially Linear Models

applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically;

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Linpack User's Guide

analyzing and solving various systems of simultaneous linear algebraic equations and linear least squares problems. This guide supports both the;

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Econometrics

, regressions, equations and diagrams to illustrate the analysis.Examine a linear and multiple regression model, ordinary least;

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Linear Models

pertaining to the linear model, starting with vector space theory and the theory of least-squares estimation. An outline of the Helmert matrix;

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Numerical Linear Algebra: An Introduction

standard material such as direct methods for solving linear systems and least-squares problems, error, stability and conditioning, basic iterative;

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Numerical Linear Algebra

standard material such as direct methods for solving linear systems and least-squares problems, error, stability and conditioning, basic iterative;

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Numerical Linear Algebra

systems of equations, spectral theory, vector and matrix norms combined with main direct and iterative numerical methods, least squares problems;

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Course In Linear Algebra With Applications, A (2nd Edition)

the Method of Least Squares. An entirely new chapter on linear programing introduces the reader to the simplex algorithm with emphasis on;

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