Robust Regression And Outlier Detection
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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
Advanced Analytics And Learning On Temporal Data
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Author : Vincent Lemaire
language : en
Publisher: Springer Nature
Release Date : 2020-01-22
Advanced Analytics And Learning On Temporal Data written by Vincent Lemaire and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-22 with Computers categories.
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
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Author : Hossein Riazoshams
language : en
Publisher: John Wiley & Sons
Release Date : 2018-06-11
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 2018-06-11 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.
Modern Methods For Robust Regression
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Author : Robert Andersen
language : en
Publisher: SAGE
Release Date : 2008
Modern Methods For Robust Regression written by Robert Andersen and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Mathematics categories.
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.
Multiple Outliers In Linear Regression
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Author : James Walter Wisnowski
language : en
Publisher:
Release Date : 1999
Multiple Outliers In Linear Regression written by James Walter Wisnowski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Outliers (Statistics) categories.
Empirical evidence suggests unusual or outlying observations in data sets are much more prevalent than one might expect; 5 to 10% on average for many industries. This research addresses multiple outliers in the linear regression model. Although reliable for a single or a few outliers, standard diagnostic techniques from an ordinary least squares (OLS) fit can fail to identify multiple outliers. The parameter estimates, diagnostic quantities and model inferences from the contaminated data set can be significantly different from those obtained with the clean data. The researcher requires a dependable method to identify and accommodate these multiple outliers. This research tests both direct methods from algorithms and indirect methods from robust regression estimators to identify multiple outliers. A comprehensive Monte Carlo simulation study evaluates the impact that outlier density and geometry, regressor variable dimension, and outlying distance have on numerous published methods. The performance study focuses on outlier configurations likely to be encountered in practice and uses a designed experiment approach. The results for each scenario provide insight and limitations in performance for each technique. Recommendations are given for each technique. OLS is the optimal regression estimator under a set of assumptions on the distribution of the error term and predictor variables. Compound robust regression estimators have been proposed as alternatives when some OLS assumptions fail. Compound estimators can accommodate multiple outliers and limit the influence of the observations with remote levels of predictor variables. This research proposes a new compound estimator that is more effective for extreme observations in X space and high dimension than currently published methods. This research also addresses the variable selection problem for compound robust regression estimators.
Data Analysis
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Author : Wolfgang A. Gaul
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Data Analysis written by Wolfgang A. Gaul and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
"Data Analysis" in the broadest sense is the general term for a field of activities of ever-increasing importance in a time called the information age. It covers new areas with such trendy labels as, e.g., data mining or web mining as well as traditional directions emphazising, e.g., classification or knowledge organization. Leading researchers in data analysis have contributed to this volume and delivered papers on aspects ranging from scientific modeling to practical application. They have devoted their latest contributions to a book edited to honor a colleague and friend, Hans-Hermann Bock, who has been active in this field for nearly thirty years.
From Data And Information Analysis To Knowledge Engineering
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Author : Myra Spiliopoulou
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-20
From Data And Information Analysis To Knowledge Engineering written by Myra Spiliopoulou and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-20 with Language Arts & Disciplines categories.
This volume collects revised versions of papers presented at the 29th Annual Conference of the Gesellschaft für Klassifikation, the German Classification Society, held at the Otto-von-Guericke-University of Magdeburg, Germany, in March 2005. In addition to traditional subjects like Classification, Clustering, and Data Analysis, converage extends to a wide range of topics relating to Computer Science: Text Mining, Web Mining, Fuzzy Data Analysis, IT Security, Adaptivity and Personalization, and Visualization.
Control Performance Assessment Theoretical Analyses And Industrial Practice
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Author : Paweł D. Domański
language : en
Publisher: Springer Nature
Release Date : 2019-09-01
Control Performance Assessment Theoretical Analyses And Industrial Practice written by Paweł D. Domański and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-01 with Technology & Engineering categories.
This book presents a comprehensive review of currently available Control Performance Assessment methods. It covers a broad range of classical and modern methods, with a main focus on assessment practice, and is intended to help practitioners learn and properly perform control assessment in the industrial reality. Further, it offers an educational guide for control engineers, who are currently in high demand in the industry. The book consists of three main parts. Firstly, a comprehensive review of available approaches is presented and discussed. The classical canon methods are extended with a discussion of nonlinear and complex alternative measures using non-Gaussian statistics, persistence and fractional calculations. Secondly, the methods’ applicability aspects are visualized with the aid of computer simulations, covering the most popular control philosophies used in the process industry. Lastly, a critical review of the methods discussed, on the basis of real-world industrial examples, rounds out the coverage.
Multiple Outliers In Linear Regression
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Author : James Walter Wisnowski
language : en
Publisher:
Release Date : 1999
Multiple Outliers In Linear Regression written by James Walter Wisnowski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Outliers (Statistics) categories.
Understanding Robust And Exploratory Data Analysis
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Author : David C. Hoaglin
language : en
Publisher: John Wiley & Sons
Release Date : 2000-06-02
Understanding Robust And Exploratory Data Analysis written by David C. Hoaglin 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 2000-06-02 with Mathematics categories.
Originally published in hardcover in 1982, this book is now offered in a Wiley Classics Library edition. A contributed volume, edited by some of the preeminent statisticians of the 20th century, Understanding of Robust and Exploratory Data Analysis explains why and how to use exploratory data analysis and robust and resistant methods in statistical practice.