Modern Methods For Robust Regression Pdf
In this study we evaluated three robust regression techniques namely least trimmed square (LTS), least absolute deviation. A Comparative Study of Three Improved Robust Regression Procedures. 426 from the population of. Modern Methods for Robust Regression, Sara Miller McCune. SAGE publications, The United.
Author by: Robert Andersen Language: en Publisher by: SAGE Format Available: PDF, ePub, Mobi Total Read: 55 Total Download: 321 File Size: 47,9 Mb Description: Geared towards both future and practising social scientists, this book takes an applied approach and offers readers empirical examples to illustrate key concepts. It includes: applied coverage of a topic that has traditionally been discussed from a theoretical standpoint; empirical examples to illustrate key concepts; a web appendix that provides readers with the data and the R-code for the examples used in the book. Author by: Peter J. Rousseeuw Language: en Publisher by: John Wiley & Sons Format Available: PDF, ePub, Mobi Total Read: 23 Total Download: 917 File Size: 47,7 Mb Description: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
'The writing style is clear and informal, and much of the discussion is oriented to application. In short, the book is a keeper.' –Mathematical Geology 'I would highly recommend the addition of this book to the libraries of both students and professionals. It is a useful textbook for the graduate student, because it emphasizes both the philosophy and practice of robustness in regression settings, and it provides excellent examples of precise, logical proofs of theorems....Even for those who are familiar with robustness, the book will be a good reference because it consolidates the research in high-breakdown affine equivariant estimators and includes an extensive 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 statistical practice.’ Rousseeuw and Leroy have included all of the necessary ingredients to make this happen.' –Journal of the American Statistical Association. Author by: Badi H. Baltagi Language: en Publisher by: Oxford University Press Format Available: PDF, ePub, Mobi Total Read: 77 Total Download: 188 File Size: 53,6 Mb Description: The Oxford Handbook of Panel Data examines new developments in the theory and applications of panel data. It includes basic topics like non-stationary panels, co-integration in panels, multifactor panel models, panel unit roots, measurement error in panels, incidental parameters and dynamic panels, spatial panels, nonparametric panel data, random coefficients, treatment effects, sample selection, count panel data, limited dependent variable panel models, unbalanced panel models with interactive effects and influential observations in panel data. Contributors to the Handbook explore applications of panel data to a wide range of topics in economics, including health, labor, marketing, trade, productivity, and macro applications in panels.
This Handbook is an informative and comprehensive guide for both those who are relatively new to the field and for those wishing to extend their knowledge to the frontier. It is a trusted and definitive source on panel data, having been edited by Professor Badi Baltagi-widely recognized as one of the foremost econometricians in the area of panel data econometrics. Professor Baltagi has successfully recruited an all-star cast of experts for each of the well-chosen topics in the Handbook.
Author by: Thomas P. Ryan Language: en Publisher by: John Wiley & Sons Format Available: PDF, ePub, Mobi Total Read: 70 Total Download: 629 File Size: 46,5 Mb Description: '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. Download Radio Fm Apk Offline more. Author by: Rebecca M. Warner Language: en Publisher by: SAGE Format Available: PDF, ePub, Mobi Total Read: 34 Total Download: 333 File Size: 49,5 Mb Description: Rebecca M. Warner’s Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression.
The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method.
Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions. Author by: Harry J. Khamis Language: en Publisher by: SAGE Format Available: PDF, ePub, Mobi Total Read: 53 Total Download: 864 File Size: 52,7 Mb Description: The Association Graph and the Multigraph for Loglinear Models will help students, particularly those studying the analysis of categorical data, to develop the ability to evaluate and unravel even the most complex loglinear models without heavy calculations or statistical software. This supplemental text reviews loglinear models, explains the association graph, and introduces the multigraph to students who may have little prior experience of graphical techniques, but have some familiarity with categorical variable modeling. The author presents logical step-by-step techniques from the point of view of the practitioner, focusing on how the technique is applied to contingency table data and how the results are interpreted.
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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. Learn more about 'The Little Green Book' - QASS Series!