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Data Fitting and Uncertainty

scientists or corresponding undergraduates who are interested in data fitting by the method of least-squares approximation, but have no or only;

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The Combination of Observations

First published in 1931, this book is the second edition of a 1917 original. The text provides an account of the method of least squares;

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Partial Least Squares Path Modeling

This edited book presents the recent developments in partial least squares-path modeling (PLS-PM) and provides a comprehensive overview;

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The Least-Squares Finite Element Method

This is the first monograph on the subject, providing a comprehensive introduction to the LSFEM method for numerical solution of PDEs;

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Least Squares Data Fitting with Applications

can use the data predictively. The main concern of Least Squares Data Fitting with Applications is how to do this on a computer with;

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Inverse Problem Theory and Methods for Model Parameter Estimation

recent developments in inverse theory, this text is a completely rewritten version of a 1987 book by the same author, and includes many;

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Mathematical Modeling and Applied Calculus

sequence. Topics that are not traditionally taught in a one-semester Calculus course, such as dimensional analysis and the method of least squares;

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An Introduction to Numerical Analysis

Fourier transform, numerical differentiation, the method of lines, boundary value problems, the conjugate gradient method, and the least squares;

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Advanced Issues in Partial Least Squares Structural Equation Modeling

A practical and applied text on PLS-SEM that combines simple explanations of complex statistical concepts with examples and case studies;

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Residual Stress Measurement and the Slitting Method

, weighted least squares fit and convergence test in stress estimation, and computer programs to facilitate the implementation of the slitting method.;

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Understanding Least Squares Estimation and Geomatics Data Analysis

Provides a modern approach to least squares estimation and data analysis for undergraduate land surveying and geomatics programs Rich;

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Adaptive Filtering

. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB (R) covers the core concepts of this important field, focusing on a vital part;

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Adaptive Filtering

. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB covers the core concepts of this important field, focusing on a vital part;

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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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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

The third edition of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) guides readers through learning and mastering;

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Econometrics

squares method, and the Gauss-Markov conditions for a best linear unbiased estimator.Understand hypothesis testing, with a null;

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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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Data Analysis

least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution;

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Partial Update Least-Square Adaptive Filtering

). Therefore, analyses for PU least-squares adaptive filter algorithms are necessary and meaningful. This monograph mostly focuses on the analyses;

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Partial Update Least-Square Adaptive Filtering

). Therefore, analyses for PU least-squares adaptive filter algorithms are necessary and meaningful. This monograph mostly focuses on the analyses;

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