Robust Nonlinear Regression

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Publisher : John Wiley & Sons
ISBN 13 : 1119010454
Total Pages : 264 pages
Book Rating : 4.56/5 ( download)

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Book Synopsis Robust Nonlinear Regression by : Hossein Riazoshams

Download or read book Robust Nonlinear Regression written by Hossein Riazoshams and published by John Wiley & Sons. This book was released on 2018-06-11 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book to discuss robust aspects of nonlinear regression—with applications using R software Robust Nonlinear Regression: with Applications using R covers a variety of theories and applications of nonlinear robust regression. It discusses both parts of the classic and robust aspects of nonlinear regression and focuses on outlier effects. It develops new methods in robust nonlinear regression and implements a set of objects and functions in S-language under SPLUS and R software. The software covers a wide range of robust nonlinear fitting and inferences, and is designed to provide facilities for computer users to define their own nonlinear models as an object, and fit models using classic and robust methods as well as detect outliers. The implemented objects and functions can be applied by practitioners as well as researchers. The book offers comprehensive coverage of the subject in 9 chapters: Theories of Nonlinear Regression and Inference; Introduction to R; Optimization; Theories of Robust Nonlinear Methods; Robust and Classical Nonlinear Regression with Autocorrelated and Heteroscedastic errors; Outlier Detection; R Packages in Nonlinear Regression; A New R Package in Robust Nonlinear Regression; and Object Sets. The first comprehensive coverage of this field covers a variety of both theoretical and applied topics surrounding robust nonlinear regression Addresses some commonly mishandled aspects of modeling R packages for both classical and robust nonlinear regression are presented in detail in the book and on an accompanying website Robust Nonlinear Regression: with Applications using R is an ideal text for statisticians, biostatisticians, and statistical consultants, as well as advanced level students of statistics.

Robust Estimation in Nonlinear Regression Models

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Publisher :
ISBN 13 :
Total Pages : 41 pages
Book Rating : 4.64/5 ( download)

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Book Synopsis Robust Estimation in Nonlinear Regression Models by : Pavel Čížek

Download or read book Robust Estimation in Nonlinear Regression Models written by Pavel Čížek and published by . This book was released on 2001 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Robust Methods and Asymptotic Theory in Nonlinear Econometrics

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Publisher : Springer Science & Business Media
ISBN 13 : 3642455298
Total Pages : 211 pages
Book Rating : 4.92/5 ( download)

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Book Synopsis Robust Methods and Asymptotic Theory in Nonlinear Econometrics by : H. J. Bierens

Download or read book Robust Methods and Asymptotic Theory in Nonlinear Econometrics written by H. J. Bierens and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Lecture Note deals with asymptotic properties, i.e. weak and strong consistency and asymptotic normality, of parameter estimators of nonlinear regression models and nonlinear structural equations under various assumptions on the distribution of the data. The estimation methods involved are nonlinear least squares estimation (NLLSE), nonlinear robust M-estimation (NLRME) and non linear weighted robust M-estimation (NLWRME) for the regression case and nonlinear two-stage least squares estimation (NL2SLSE) and a new method called minimum information estimation (MIE) for the case of structural equations. The asymptotic properties of the NLLSE and the two robust M-estimation methods are derived from further elaborations of results of Jennrich. Special attention is payed to the comparison of the asymptotic efficiency of NLLSE and NLRME. It is shown that if the tails of the error distribution are fatter than those of the normal distribution NLRME is more efficient than NLLSE. The NLWRME method is appropriate if the distributions of both the errors and the regressors have fat tails. This study also improves and extends the NL2SLSE theory of Amemiya. The method involved is a variant of the instrumental variables method, requiring at least as many instrumental variables as parameters to be estimated. The new MIE method requires less instrumental variables. Asymptotic normality can be derived by employing only one instrumental variable and consistency can even be proved with out using any instrumental variables at all.

Robust Estimation in Nonlinear Regression and Limited Dependent Variable Models

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Publisher :
ISBN 13 :
Total Pages : 86 pages
Book Rating : 4.43/5 ( download)

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Book Synopsis Robust Estimation in Nonlinear Regression and Limited Dependent Variable Models by : Pavel Čížek

Download or read book Robust Estimation in Nonlinear Regression and Limited Dependent Variable Models written by Pavel Čížek and published by . This book was released on 2001 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Robust Regression

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Publisher : Routledge
ISBN 13 : 1351418289
Total Pages : 310 pages
Book Rating : 4.87/5 ( download)

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Book Synopsis Robust Regression by : Kenneth D. Lawrence

Download or read book Robust Regression written by Kenneth D. Lawrence and published by Routledge. This book was released on 2019-05-20 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weight each observation discusses generalized properties of Lp-estimators. Includes an algorithm for identifying outliers using least absolute value criterion in regression modeling reviews redescending M-estimators studies Li linear regression proposes the best linear unbiased estimators for fixed parameters and random errors in the mixed linear model summarizes known properties of Li estimators for time series analysis examines ordinary least squares, latent root regression, and a robust regression weighting scheme and evaluates results from five different robust ridge regression estimators.

Robust Regression

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Publisher : Routledge
ISBN 13 : 1351418270
Total Pages : 320 pages
Book Rating : 4.70/5 ( download)

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Book Synopsis Robust Regression by : Kenneth D. Lawrence

Download or read book Robust Regression written by Kenneth D. Lawrence and published by Routledge. This book was released on 2019-05-20 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weight each observation discusses generalized properties of Lp-estimators. Includes an algorithm for identifying outliers using least absolute value criterion in regression modeling reviews redescending M-estimators studies Li linear regression proposes the best linear unbiased estimators for fixed parameters and random errors in the mixed linear model summarizes known properties of Li estimators for time series analysis examines ordinary least squares, latent root regression, and a robust regression weighting scheme and evaluates results from five different robust ridge regression estimators.

Fitting Models to Biological Data Using Linear and Nonlinear Regression

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Publisher : Oxford University Press
ISBN 13 : 9780198038344
Total Pages : 352 pages
Book Rating : 4.48/5 ( download)

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Book Synopsis Fitting Models to Biological Data Using Linear and Nonlinear Regression by : Harvey Motulsky

Download or read book Fitting Models to Biological Data Using Linear and Nonlinear Regression written by Harvey Motulsky and published by Oxford University Press. This book was released on 2004-05-27 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.

Nonlinear Multivariate Analysis

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Publisher :
ISBN 13 : 9788126545117
Total Pages : 579 pages
Book Rating : 4.19/5 ( download)

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Book Synopsis Nonlinear Multivariate Analysis by :

Download or read book Nonlinear Multivariate Analysis written by and published by . This book was released on 1990 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Modern Methods for Robust Regression

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Publisher : SAGE
ISBN 13 : 1412940729
Total Pages : 129 pages
Book Rating : 4.26/5 ( download)

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Book Synopsis Modern Methods for Robust Regression by : Robert Andersen

Download or read book Modern Methods for Robust Regression written by Robert Andersen and published by SAGE. This book was released on 2008 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering an in-depth treatment of robust and resistant regression, this volume takes an applied approach and offers readers empirical examples to illustrate key concepts.

Robust Non-Linear Regression Using The Dogleg Algorithm

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.79/5 ( download)

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Book Synopsis Robust Non-Linear Regression Using The Dogleg Algorithm by : Roy E. Welsch

Download or read book Robust Non-Linear Regression Using The Dogleg Algorithm written by Roy E. Welsch and published by . This book was released on 1975 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: What are the statistical and computational problems associated with robust nonlinear regression? This paper presents a number of possible approaches to these problems and develops a particular algorithm based on the work of Powell and Dennis.