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Adaptive Regression for Modeling Nonlinear Relationships

when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for;

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Adaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning;

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Statistical Regression Modeling with R

This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear;

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Statistical Regression Modeling with R

This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear;

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Nonlinear Regression Modeling

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Robust Nonlinear Regression

mishandled aspects of modeling R packages for both classical and robust nonlinear regression are presented in detail in the book and on an;

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Applied Regression and Modeling

regression analysis with applications, and (3) regression and modeling including the second order models, nonlinear regression, and interaction;

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Modeling and Adaptive Nonlinear Control of Electric Motors

motors. The book reports new global robust adaptive designs for motors and provides new tools for control designs, with an emphasis on stepper;

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Regression Modeling: Methods, Theory, and Computation with SAS

, nonlinear least squares, and time-series regression issues. For most of the regression methods, the author includes SAS procedure code, enabling;

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Regression Modeling: Methods, Theory, and Computation with SAS

, nonlinear least squares, and time-series regression issues. For most of the regression methods, the author includes SAS procedure code, enabling;

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Nonlinear Regression Analysis and Its Applications

...highly recommend[ed] ...for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models;

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Nonlinear and Adaptive Control Systems

An adaptive system for linear systems with unknown parameters is a nonlinear system. The analysis of such adaptive systems requires similar;

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Nonlinear Computer Modeling of Chemical and Biochemical Data

Modeling of Chemical and Biochemical Data presents the fundamental basis and procedures of data modeling by computer using nonlinear regression;

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Adaptive Business Intelligence

. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy;

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Adaptive Business Intelligence

. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy;

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Alternative Methods of Regression

presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and;

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Regression Modeling Strategies

missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the;

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Regression Models as a Tool in Medical Research

results is often challenging for beginners. Regression Models as a Tool in Medical Research presents the fundamental concepts and important;

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Regression Models As A Tool In Medical Research

results is often challenging for beginners. Regression Models as a Tool in Medical Research presents the fundamental concepts and important;

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Artificial Intelligence in Civil Engineering

, Gaussian Process Regression, Logistic Regression) for solving different problems in civil engineering.The book is very useful for civil engineers.;

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Logistic Regression Inside and Out

If you have a yes or no question, then you can probably answer it with a logistic regression model. Logistic regression is most appropriate;

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Intelligence For Nonlinear Dynamics And Synchronization

models in nonlinear science (for example, adaptive control, signal processing, medical diagnostic, pattern formation, living systems, etc.).This;

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Nonlinear Regression with R

- Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.;

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Limit Theorems For Nonlinear Cointegrating Regression

This book provides the limit theorems that can be used in the development of nonlinear cointegrating regression. The topics include weak;

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Nonlinear Regression Modeling for Engineering Applications

book details methods of nonlinear regression, computational algorithms,model validation, interpretation of residuals, and useful experimental;

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Adaptive Regression

While there have been a large number of estimation methods proposed and developed for linear regression, none has proved good for all;

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Introduction to Multivariate Analysis

Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling;

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