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Modern Methods for Robust Regression

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Release : 2007-09-06
Genre : Social Science
Kind : eBook
Book Rating : 564/5 ( 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 2007-09-06. Available in PDF, EPUB and Kindle. Book excerpt: Modern Methods for Robust Regression offers a brief but in-depth treatment of various methods for detecting and properly handling influential cases in regression analysis. This volume, geared toward both future and practicing social scientists, is unique in that it takes an applied approach and offers readers empirical examples to illustrate key concepts. It is ideal for readers who are interested in the issues related to outliers and influential cases. Key Features Defines key terms necessary to understanding the robustness of an estimator: Because they form the basis of robust regression techniques, the book also deals with various measures of location and scale. Addresses the robustness of validity and efficiency: After having described the robustness of validity for an estimator, the author discusses its efficiency. Focuses on the impact of outliers: The book compares the robustness of a wide variety of estimators that attempt to limit the influence of unusual observations. Gives an overview of some traditional techniques: Both formal statistical tests and graphical methods detect influential cases in the general linear model. Offers a Web appendix: This volume provides readers with the data and the R code for the examples used in the book. Intended Audience This is an excellent text for intermediate and advanced Quantitative Methods and Statistics courses offered at the graduate level across the social sciences.

Modern Methods for Robust Regression

Download Modern Methods for Robust Regression PDF Online Free

Author :
Release : 2008
Genre : Electronic books
Kind : eBook
Book Rating : 109/5 ( reviews)

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Book Synopsis Modern Methods for Robust Regression by : Robert Andersen (Ph. D.)

Download or read book Modern Methods for Robust Regression written by Robert Andersen (Ph. D.). 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.

Modern Methods for Robust Regression

Download Modern Methods for Robust Regression PDF Online Free

Author :
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.

Modern Regression Methods

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Author :
Release : 2008-11-10
Genre : Mathematics
Kind : eBook
Book Rating : 864/5 ( reviews)

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Book Synopsis Modern Regression Methods by : Thomas P. Ryan

Download or read book Modern Regression Methods written by Thomas P. Ryan. This book was released on 2008-11-10. Available in PDF, EPUB and Kindle. Book excerpt: "Over the years, I have had the opportunity to teach several regression courses, and I cannot think of a better undergraduate text than this one." —The American Statistician "The book is well written and has many exercises. It can serve as a very good textbook for scientists and engineers, with only basic statistics as a prerequisite. I also highly recommend it to practitioners who want to solve real-life prediction problems." (Computing Reviews) Modern Regression Methods, Second Edition maintains the accessible organization, breadth of coverage, and cutting-edge appeal that earned its predecessor the title of being one of the top five books for statisticians by an Amstat News book editor in 2003. This new edition has been updated and enhanced to include all-new information on the latest advances and research in the evolving field of regression analysis. The book provides a unique treatment of fundamental regression methods, such as diagnostics, transformations, robust regression, and ridge regression. Unifying key concepts and procedures, this new edition emphasizes applications to provide a more hands-on and comprehensive understanding of regression diagnostics. New features of the Second Edition include: A revised chapter on logistic regression, including improved methods of parameter estimation A new chapter focusing on additional topics of study in regression, including quantile regression, semiparametric regression, and Poisson regression A wealth of new and updated exercises with worked solutions An extensive FTP site complete with Minitab macros, which allow the reader to compute analyses, and specialized procedures Updated references at the end of each chapter that direct the reader to the appropriate resources for further study An accessible guide to state-of-the-art regression techniques, Modern Regression Methods, Second Edition is an excellent book for courses in regression analysis at the upper-undergraduate and graduate levels. It is also a valuable reference for practicing statisticians, engineers, and physical scientists.

Introduction to Robust Estimation and Hypothesis Testing

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Author :
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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