Robust Nonlinear Regression

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Robust Nonlinear Regression

Hossein Riazoshams,Habshah Midi,Gebrenegus Ghilagaber
Robust Nonlinear Regression Book PDF

Author : Hossein Riazoshams,Habshah Midi,Gebrenegus Ghilagaber
Publisher : John Wiley & Sons
Page : 264 pages
File Size : 40,9 Mb
Release : 2018-06-11
Category : Mathematics
ISBN : 9781119010456

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Robust Nonlinear Regression by Hossein Riazoshams,Habshah Midi,Gebrenegus Ghilagaber Pdf

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 Nonlinear Regression

Hossein Riazoshams,Habshah Midi,Gebrenegus Ghilagaber
Robust Nonlinear Regression Book PDF

Author : Hossein Riazoshams,Habshah Midi,Gebrenegus Ghilagaber
Publisher : John Wiley & Sons
Page : 264 pages
File Size : 43,9 Mb
Release : 2018-06-11
Category : Mathematics
ISBN : 9781119010449

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Robust Nonlinear Regression by Hossein Riazoshams,Habshah Midi,Gebrenegus Ghilagaber Pdf

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 Non-Linear Regression Using The Dogleg Algorithm

Roy E. Welsch
Robust Non Linear Regression Using The Dogleg Algorithm Book PDF

Author : Roy E. Welsch
Publisher : Unknown
Page : 0 pages
File Size : 43,6 Mb
Release : 1975
Category : Electronic
ISBN : OCLC:1194655579

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Robust Non-Linear Regression Using The Dogleg Algorithm by Roy E. Welsch Pdf

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.

Robust Regression

Kenneth D. Lawrence
Robust Regression Book PDF

Author : Kenneth D. Lawrence
Publisher : Routledge
Page : 310 pages
File Size : 42,7 Mb
Release : 2019-05-20
Category : Mathematics
ISBN : 9781351418287

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Robust Regression by Kenneth D. Lawrence Pdf

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.

Nonlinear Regression with R

Christian Ritz,Jens Carl Streibig
Nonlinear Regression with R Book PDF

Author : Christian Ritz,Jens Carl Streibig
Publisher : Springer Science & Business Media
Page : 151 pages
File Size : 46,5 Mb
Release : 2008-12-11
Category : Mathematics
ISBN : 9780387096162

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Nonlinear Regression with R by Christian Ritz,Jens Carl Streibig Pdf

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

Robust Methods and Asymptotic Theory in Nonlinear Econometrics

H. J. Bierens
Robust Methods and Asymptotic Theory in Nonlinear Econometrics Book PDF

Author : H. J. Bierens
Publisher : Springer Science & Business Media
Page : 211 pages
File Size : 49,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783642455292

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Robust Methods and Asymptotic Theory in Nonlinear Econometrics by H. J. Bierens Pdf

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 Diagnostic Regression Analysis

Anthony Atkinson,Marco Riani
Robust Diagnostic Regression Analysis Book PDF

Author : Anthony Atkinson,Marco Riani
Publisher : Springer Science & Business Media
Page : 342 pages
File Size : 46,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461211600

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Robust Diagnostic Regression Analysis by Anthony Atkinson,Marco Riani Pdf

Graphs are used to understand the relationship between a regression model and the data to which it is fitted. The authors develop new, highly informative graphs for the analysis of regression data and for the detection of model inadequacies. As well as illustrating new procedures, the authors develop the theory of the models used, particularly for generalized linear models. The book provides statisticians and scientists with a new set of tools for data analysis. Software to produce the plots is available on the authors website.

Nonlinear Regression, Functional Relations and Robust Methods

Helga Bunke,Olaf Bunke
Nonlinear Regression Functional Relations and Robust Methods Book PDF

Author : Helga Bunke,Olaf Bunke
Publisher : Unknown
Page : 458 pages
File Size : 47,9 Mb
Release : 1989
Category : Mathematics
ISBN : UCSC:32106009913168

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Nonlinear Regression, Functional Relations and Robust Methods by Helga Bunke,Olaf Bunke Pdf

This book, the second volume in a three part work, provides a comprehensive and unified account of nonlinear regression analysis, functional and structural relations, and of nonparametric and robust estimators. Research in these areas has been stimulated by the increase in computational capabilities and this volume will therefore be of great interest to researchers in statistics as well as applied statisticians working in industry. The material provided includes recent work from German and Russian sources, as well as from English-speaking sources, and the treatment throughout is mathematically rigorous but accessible. The text will benefit rsearchers in statistics and applied statisticians working in industry.

Directions in Robust Statistics and Diagnostics

Werner Stahel,Sanford Weisberg
Directions in Robust Statistics and Diagnostics Book PDF

Author : Werner Stahel,Sanford Weisberg
Publisher : Springer Science & Business Media
Page : 384 pages
File Size : 50,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461244448

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Directions in Robust Statistics and Diagnostics by Werner Stahel,Sanford Weisberg Pdf

This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA 1989 summer program "Robustness, Diagnostics, Computing and Graphics in Statistics". An important objective of the organizers was to draw a broad set of statisticians working in robustness or diagnostics into collaboration on the challenging problems in these areas, particularly on the interface between them. We thank the organizers of the robustness and diagnostics program Noel Cressie, Thomas P. Hettmansperger, Peter J. Huber, R. Douglas Martin, and especially Werner Stahel and Sanford Weisberg who edited the proceedings. A vner Friedman Willard Miller, Jr. PREFACE Central themes of all statistics are estimation, prediction, and making decisions under uncertainty. A standard approach to these goals is through parametric mod elling. Parametric models can give a problem sufficient structure to allow standard, well understood paradigms to be applied to make the required inferences. If, how ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers. In the last quarter century, particularly with the advent of readily available computing, more attention has been paid to the problem of inference when the parametric model used is not correctly specified.

Nonlinear Regression

George A. F. Seber,C. J. Wild
Nonlinear Regression Book PDF

Author : George A. F. Seber,C. J. Wild
Publisher : John Wiley & Sons
Page : 768 pages
File Size : 50,9 Mb
Release : 2005-02-25
Category : Mathematics
ISBN : 9780471725305

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Nonlinear Regression by George A. F. Seber,C. J. Wild Pdf

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. From the Reviews of Nonlinear Regression "A very good book and an important one in that it is likely to become a standard reference for all interested in nonlinear regression; and I would imagine that any statistician concerned with nonlinear regression would want a copy on his shelves." –The Statistician "Nonlinear Regression also includes a reference list of over 700 entries. The compilation of this material and cross-referencing of it is one of the most valuable aspects of the book. Nonlinear Regression can provide the researcher unfamiliar with a particular specialty area of nonlinear regression an introduction to that area of nonlinear regression and access to the appropriate references . . . Nonlinear Regression provides by far the broadest discussion of nonlinear regression models currently available and will be a valuable addition to the library of anyone interested in understanding and using such models including the statistical researcher." –Mathematical Reviews

An R and S-Plus Companion to Applied Regression

John Fox
An R and S Plus Companion to Applied Regression Book PDF

Author : John Fox
Publisher : SAGE
Page : 332 pages
File Size : 43,9 Mb
Release : 2002-06-05
Category : Mathematics
ISBN : 0761922806

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An R and S-Plus Companion to Applied Regression by John Fox Pdf

"This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. It meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics, and useful instructions on writing customized functions. " —JEFF GILL, University of Florida, Gainesville

Fitting Models to Biological Data Using Linear and Nonlinear Regression

Harvey Motulsky,Arthur Christopoulos
Fitting Models to Biological Data Using Linear and Nonlinear Regression Book PDF

Author : Harvey Motulsky,Arthur Christopoulos
Publisher : Oxford University Press
Page : 352 pages
File Size : 43,5 Mb
Release : 2004-05-27
Category : Mathematics
ISBN : 0198038348

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Fitting Models to Biological Data Using Linear and Nonlinear Regression by Harvey Motulsky,Arthur Christopoulos Pdf

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.