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Robust Statistical Procedures

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Robust Statistical Procedures

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Author : Peter J. Huber
language : en
Publisher: SIAM
Release Date : 1996-01-01

Robust Statistical Procedures written by Peter J. Huber and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-01-01 with Mathematics categories.

Modern Historiographyis the essential introduction to the history of historical writing. It explains the broad philosophical background to the different historians and historical schools of the modern era. In a unique overview of modern historiography, the book includes surveys on the Enlightenment and Counter Enlightenment; Romanticism; the voice of Science and the process of secularization within Western intellectual thought; the influence of, and broadening contact with, the New World; theAnnalesschool in France; and the effects of the repression and exile of the inter-war years and the Post-War 'moods.'Modern Historiographyprovides a clear and concise account of this modern period of historical writing.

Robust Statistical Procedures

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Author : Jana Jurecková
language : en
Publisher: John Wiley & Sons
Release Date : 1996-04-19

Robust Statistical Procedures written by Jana Jurecková and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-04-19 with Mathematics categories.

A broad and unified methodology for robust statistics—with exciting new applications Robust statistics is one of the fastest growing fields in contemporary statistics. It is also one of the more diverse and sometimes confounding areas, given the many different assessments and interpretations of robustness by theoretical and applied statisticians. This innovative book unifies the many varied, yet related, concepts of robust statistics under a sound theoretical modulation. It seamlessly integrates asymptotics and interrelations, and provides statisticians with an effective system for dealing with the interrelations between the various classes of procedures. Drawing on the expertise of researchers from around the world, and covering over a decade's worth of developments in the field, Robust Statistical Procedures: Asymptotics and Interrelations: Discusses both theory and applications in its two parts, from the fundamentals to robust statistical inference Thoroughly explores the interrelations between diverse classes of procedures, unlike any other book Compares nonparametric procedures with robust statistics, explaining in detail asymptotic representations for various estimators Provides a timesaving list of mathematical tools for the problems under discussion Keeps mathematical abstractions to a minimum, in spite of its largely theoretical content Includes useful problems and exercises at the end of each chapter Offers strategies for more complex models when using robust statistical procedures Self-contained and rounded in approach, this book is invaluable for both applied statisticians and theoretical researchers; for graduate students in mathematical statistics; and for anyone interested in the influence of this methodology.

Robust Statistics

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Author : Ricardo A. Maronna
language : en
Publisher: John Wiley & Sons
Release Date : 2019-01-04

Robust Statistics written by Ricardo A. Maronna and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-04 with Mathematics categories.

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from standard distributions. Robust statistical methods take into account these deviations when estimating the parameters of parametric models, thus increasing the reliability of fitted models and associated inference. This new, second edition of Robust Statistics: Theory and Methods (with R) presents a broad coverage of the theory of robust statistics that is integrated with computing methods and applications. Updated to include important new research results of the last decade and focus on the use of the popular software package R, it features in-depth coverage of the key methodology, including regression, multivariate analysis, and time series modeling. The book is illustrated throughout by a range of examples and applications that are supported by a companion website featuring data sets and R code that allow the reader to reproduce the examples given in the book. Unlike other books on the market, Robust Statistics: Theory and Methods (with R) offers the most comprehensive, definitive, and up-to-date treatment of the subject. It features chapters on estimating location and scale; measuring robustness; linear regression with fixed and with random predictors; multivariate analysis; generalized linear models; time series; numerical algorithms; and asymptotic theory of M-estimates. Explains both the use and theoretical justification of robust methods Guides readers in selecting and using the most appropriate robust methods for their problems Features computational algorithms for the core methods Robust statistics research results of the last decade included in this 2nd edition include: fast deterministic robust regression, finite-sample robustness, robust regularized regression, robust location and scatter estimation with missing data, robust estimation with independent outliers in variables, and robust mixed linear models. Robust Statistics aims to stimulate the use of robust methods as a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. It is an ideal resource for researchers, practitioners, and graduate students in statistics, engineering, computer science, and physical and social sciences.

Robust Statistical Methods With R

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Author : Jana Jureckova
language : en
Publisher: CRC Press
Release Date : 2005-11-29

Robust Statistical Methods With R written by Jana Jureckova and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-11-29 with Mathematics categories.

Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systemati

Robust Nonparametric Statistical Methods

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Author : Thomas P. Hettmansperger
language : en
Publisher: Hodder Education
Release Date : 1998

Robust Nonparametric Statistical Methods written by Thomas P. Hettmansperger and has been published by Hodder Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Mathematics categories.

Based in ranks of the data, this book offers an alternative to the traditional least squares approach. Topics include one- and two-sample location models, linear models (including multiple regression and designed experiments), and multivariate models. Rank tests and estimates for all models are developed, including bounded influence and high breakdown methods. Emphasis is on efficiency and robustness and all methods are illustrated on data sets.

Robust Methods In Biostatistics

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Author : Stephane Heritier
language : en
Publisher: John Wiley & Sons
Release Date : 2009-05-11

Robust Methods In Biostatistics written by Stephane Heritier and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-11 with Medical categories.

Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated models as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general classes of models: Linear regression Generalized linear models Linear mixed models Marginal longitudinal data models Cox survival analysis model The methods are introduced both at a theoretical and applied level within the framework of each general class of models, with a particular emphasis put on practical data analysis. This book is of particular use for research students,applied statisticians and practitioners in the health field interested in more stable statistical techniques. An accompanying website provides R code for computing all of the methods described, as well as for analyzing all the datasets used in the book.

Introduction To Robust Estimation And Hypothesis Testing

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Author : Rand R. Wilcox
language : en
Publisher: Academic Press
Release Date : 2011-12-14

Introduction To Robust Estimation And Hypothesis Testing written by Rand R. Wilcox and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-14 with Mathematics categories.

This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables. - Covers latest developments in robust regression - Covers latest improvements in ANOVA - Includes newest rank-based methods - Describes and illustrated easy to use software

Robust Statistics

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Author : Frank R. Hampel
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20

Robust Statistics written by Frank R. Hampel and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Mathematics categories.

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. "This is a nice book containing a wealth of information, much ofit due to the authors. . . . If an instructor designing such acourse wanted a textbook, this book would be the best choiceavailable. . . . There are many stimulating exercises, and the bookalso contains an excellent index and an extensive list ofreferences." —Technometrics "[This] book should be read carefully by anyone who isinterested in dealing with statistical models in a realisticfashion." —American Scientist Introducing concepts, theory, and applications, RobustStatistics is accessible to a broad audience, avoidingallusions to high-powered mathematics while emphasizing ideas,heuristics, and background. The text covers the approach based onthe influence function (the effect of an outlier on an estimater,for example) and related notions such as the breakdown point. Italso treats the change-of-variance function, fundamental conceptsand results in the framework of estimation of a single parameter,and applications to estimation of covariance matrices andregression parameters.

Robust Statistical Procedures

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Author : Peter J. Huber
language : en
Publisher: SIAM
Release Date : 1996-01-01

Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition.

Robust Regression And Outlier Detection

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Author : Peter J. Rousseeuw
language : en
Publisher: John Wiley & Sons
Release Date : 2005-02-25

Robust Regression And Outlier Detection written by Peter J. Rousseeuw and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-25 with Mathematics categories.

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

Robust Statistical Procedures

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