Robust Correlation


Robust Correlation
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Robust Correlation


Robust Correlation
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Author : Georgy L. Shevlyakov
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-19

Robust Correlation written by Georgy L. Shevlyakov 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 2016-09-19 with Mathematics categories.


This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data. Key features: Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working in various fields. Focuses on implementation of methodology and application of robust correlation with R. Introduces the main approaches in robust statistics, such as Huber’s minimax approach and Hampel’s approach based on influence functions. Explores various robust estimates of the correlation coefficient including the minimax variance and bias estimates as well as the most B- and V-robust estimates. Contains applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data. Includes an accompanying website featuring computer code and datasets Features exercises and examples throughout the text using both small and large data sets. Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.



On Nonparametric Tests Of Independence And Robust Canonical Correlation Analysis


On Nonparametric Tests Of Independence And Robust Canonical Correlation Analysis
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Author : Sara Taskinen
language : en
Publisher:
Release Date : 2003

On Nonparametric Tests Of Independence And Robust Canonical Correlation Analysis written by Sara Taskinen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Multivariate analysis categories.




Robustness In Data Analysis


Robustness In Data Analysis
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Author : Georgy L. Shevlyakov
language : en
Publisher: Walter de Gruyter
Release Date : 2011-12-07

Robustness In Data Analysis written by Georgy L. Shevlyakov and has been published by Walter de Gruyter this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-07 with Mathematics categories.


The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.



Robust Nonlinear Regression


Robust Nonlinear Regression
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Author : Hossein Riazoshams
language : en
Publisher: John Wiley & Sons
Release Date : 2018-08-20

Robust Nonlinear Regression written by Hossein Riazoshams 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 2018-08-20 with Mathematics categories.


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


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



T Statistic Based Correlation And Heterogeneity Robust Inference


T Statistic Based Correlation And Heterogeneity Robust Inference
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Author : Rustam Ibragimov
language : en
Publisher:
Release Date : 2007

T Statistic Based Correlation And Heterogeneity Robust Inference written by Rustam Ibragimov and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.




Robust Multivariate Analysis


Robust Multivariate Analysis
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Author : David J. Olive
language : en
Publisher: Springer
Release Date : 2017-11-28

Robust Multivariate Analysis written by David J. Olive and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-28 with Mathematics categories.


This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author’s website.



Robust Portfolio Optimization And Management


Robust Portfolio Optimization And Management
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Author : Frank J. Fabozzi
language : en
Publisher: John Wiley & Sons
Release Date : 2007-06-04

Robust Portfolio Optimization And Management written by Frank J. Fabozzi 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 2007-06-04 with Business & Economics categories.


Praise for Robust Portfolio Optimization and Management "In the half century since Harry Markowitz introduced his elegant theory for selecting portfolios, investors and scholars have extended and refined its application to a wide range of real-world problems, culminating in the contents of this masterful book. Fabozzi, Kolm, Pachamanova, and Focardi deserve high praise for producing a technically rigorous yet remarkably accessible guide to the latest advances in portfolio construction." --Mark Kritzman, President and CEO, Windham Capital Management, LLC "The topic of robust optimization (RO) has become 'hot' over the past several years, especially in real-world financial applications. This interest has been sparked, in part, by practitioners who implemented classical portfolio models for asset allocation without considering estimation and model robustness a part of their overall allocation methodology, and experienced poor performance. Anyone interested in these developments ought to own a copy of this book. The authors cover the recent developments of the RO area in an intuitive, easy-to-read manner, provide numerous examples, and discuss practical considerations. I highly recommend this book to finance professionals and students alike." --John M. Mulvey, Professor of Operations Research and Financial Engineering, Princeton University



Correlation Clustering


Correlation Clustering
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Author : Francesco Bonchi
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2022-03-08

Correlation Clustering written by Francesco Bonchi and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-08 with Computers categories.


Given a set of objects and a pairwise similarity measure between them, the goal of correlation clustering is to partition the objects in a set of clusters to maximize the similarity of the objects within the same cluster and minimize the similarity of the objects in different clusters. In most of the variants of correlation clustering, the number of clusters is not a given parameter; instead, the optimal number of clusters is automatically determined. Correlation clustering is perhaps the most natural formulation of clustering: as it just needs a definition of similarity, its broad generality makes it applicable to a wide range of problems in different contexts, and, particularly, makes it naturally suitable to clustering structured objects for which feature vectors can be difficult to obtain. Despite its simplicity, generality, and wide applicability, correlation clustering has so far received much more attention from an algorithmic-theory perspective than from the data-mining community. The goal of this lecture is to show how correlation clustering can be a powerful addition to the toolkit of a data-mining researcher and practitioner, and to encourage further research in the area.



Introduction To Robust Estimation And Hypothesis Testing


Introduction To Robust Estimation And Hypothesis Testing
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Author : Rand R. Wilcox
language : en
Publisher: Academic Press
Release Date : 2012-01-12

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 2012-01-12 with Mathematics categories.


"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"--