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Robust Regression and Outlier Detection

2005-02-25 Mathematics
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Release : 2005-02-25
Genre : Mathematics
Kind : eBook
Book Rating : 374/5 ( reviews)

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Book Synopsis Robust Regression and Outlier Detection by : Peter J. Rousseeuw

Download or read book Robust Regression and Outlier Detection written by Peter J. Rousseeuw. This book was released on 2005-02-25. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selectedbooks that have been made more accessible to consumers in an effortto increase global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "The writing style is clear and informal, and much of thediscussion is oriented to application. In short, the book is akeeper." –Mathematical Geology "I would highly recommend the addition of this book to thelibraries of both students and professionals. It is a usefultextbook for the graduate student, because it emphasizes both thephilosophy and practice of robustness in regression settings, andit provides excellent examples of precise, logical proofs oftheorems. . . .Even for those who are familiar with robustness, thebook will be a good reference because it consolidates the researchin high-breakdown affine equivariant estimators and includes anextensive bibliography in robust regression, outlier diagnostics,and related methods. The aim of this book, the authors tell us, is‘to make robust regression available for everyday statisticalpractice.’ Rousseeuw and Leroy have included all of thenecessary ingredients to make this happen." –Journal of the American Statistical Association

Modern Methods for Robust Regression

2008 Mathematics
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Release : 2008
Genre : Mathematics
Kind : eBook
Book Rating : 729/5 ( reviews)

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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. This book was released on 2008. 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.

Advanced Analytics and Learning on Temporal Data

2020-01-22 Computers
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Release : 2020-01-22
Genre : Computers
Kind : eBook
Book Rating : 985/5 ( reviews)

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Book Synopsis Advanced Analytics and Learning on Temporal Data by : Vincent Lemaire

Download or read book Advanced Analytics and Learning on Temporal Data written by Vincent Lemaire. This book was released on 2020-01-22. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data.

Robust Nonlinear Regression

2018-06-11 Mathematics
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Release : 2018-06-11
Genre : Mathematics
Kind : eBook
Book Rating : 454/5 ( reviews)

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Book Synopsis Robust Nonlinear Regression by : Hossein Riazoshams

Download or read book Robust Nonlinear Regression written by Hossein Riazoshams. This book was released on 2018-06-11. 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.

Introduction to Robust Estimation and Hypothesis Testing

2012-01-12 Mathematics
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Release : 2012-01-12
Genre : Mathematics
Kind : eBook
Book Rating : 838/5 ( reviews)

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Book Synopsis Introduction to Robust Estimation and Hypothesis Testing by : Rand R. Wilcox

Download or read book Introduction to Robust Estimation and Hypothesis Testing written by Rand R. Wilcox. This book was released on 2012-01-12. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--

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