Resampling Methods
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Resampling Methods For Dependent Data
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Author : S. N. Lahiri
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Resampling Methods For Dependent Data written by S. N. Lahiri 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 2013-03-09 with Mathematics categories.
By giving a detailed account of bootstrap methods and their properties for dependent data, this book provides illustrative numerical examples throughout. The book fills a gap in the literature covering research on re-sampling methods for dependent data that has witnessed vigorous growth over the last two decades but remains scattered in various statistics and econometrics journals. It can be used as a graduate level text and also as a research monograph for statisticians and econometricians.
Resampling Methods
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Author : Phillip I. Good
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-12-31
Resampling Methods written by Phillip I. Good 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 2006-12-31 with Mathematics categories.
This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware. New to the third edition are additional program listings and screen shots of C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-Plus, Stata, or StatXact, which accompany each resampling procedure. A glossary and solutions to selected exercises have also been added. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.
Resampling Methods
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Author : Phillip I. Good
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Resampling Methods written by Phillip I. Good 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 2013-03-14 with Computers categories.
"...the author has packaged an excellent and modern set of topics around the development and use of quantitative models...the author has the capability to work at a more modest level. He does that very effectively in this 2nd Edition... If you need to learn about resampling, this book would be a good place to start." -- Technometrics This work is a practical, table-free introduction to data analysis using the bootstrap, cross-validation, and permutation tests; new to the second edition are several additional examples and a chapter dedicated to regression, data mining techniques, and their limitations. The book’s many exercises, practical data sets, and use of free shareware make it an essential resource for students and teachers, as well as industrial statisticians, consultants, and research professionals.
Permutation Tests
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Author : Phillip Good
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Permutation Tests written by Phillip Good 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 2013-04-17 with Mathematics categories.
A step-by-step manual on the application of permutation tests in biology, business, medicine, science, and engineering. Its intuitive and informal style make it ideal for students and researchers, whether experienced or coming to these resampling methods for the first time. The real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are all dealt with at length. This new edition has more than 100 additional pages, and includes streamlined statistics for the k-sample comparison and analysis of variance plus expanded sections on computational techniques, multiple comparisons, multiple regression, comparing variances, and testing interactions in balanced designs. The comprehensive author and subject indexes, plus an expert-system guide to methods, provide for further ease of use, while the exercises at the end of every chapter have been supplemented with drills and a number of graduate-level thesis problems.
Introduction To Statistics Through Resampling Methods And R
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Author : Phillip I. Good
language : en
Publisher: John Wiley & Sons
Release Date : 2013-02-11
Introduction To Statistics Through Resampling Methods And R written by Phillip I. Good 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 2013-02-11 with Mathematics categories.
A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.
Resampling Methods
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Author : Phillip Good
language : en
Publisher:
Release Date : 2005
Resampling Methods written by Phillip Good and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Monte Carlo Simulation And Resampling Methods For Social Science
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Author : Thomas M. Carsey
language : en
Publisher: SAGE Publications
Release Date : 2013-08-05
Monte Carlo Simulation And Resampling Methods For Social Science written by Thomas M. Carsey and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-05 with Social Science categories.
Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.
Resampling Based Multiple Testing
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Author : Peter H. Westfall
language : en
Publisher: John Wiley & Sons
Release Date : 1993-01-12
Resampling Based Multiple Testing written by Peter H. Westfall 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 1993-01-12 with Mathematics categories.
Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power.
Introduction To Statistics Through Resampling Methods And R S Plus
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Author : Phillip I. Good
language : en
Publisher: John Wiley & Sons
Release Date : 2012-01-20
Introduction To Statistics Through Resampling Methods And R S Plus written by Phillip I. Good 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 2012-01-20 with Mathematics categories.
Stimulate learning through discovery With its emphasis on the discovery method, this book allows readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers will quickly master and learn to apply statistical methods, such as bootstrap, decision trees, and permutations, to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including: Tests and estimation procedures for one, two, and multiple samples Model building Multivariate analysis Complex experimental design Throughout the text, the R programming language is used to illustrate new concepts and assist readers in completing exercises. Readers may download the freely available R programming language from the Internet or take advantage of the menu-driven S-PLUS® program. Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided: More than two hundred exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills Companion FTP site provides access to all data sets and programs discussed in the text Dozens of thought-provoking questions in the final chapter, Problem Solving, assist readers in applying statistics to address real-life problems Instructor's manual provides answers to exercises Helpful appendices include an introduction to S-PLUS® features This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited for both students and practitioners.
Monte Carlo Simulation And Resampling Methods For Social Science
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Author : Thomas M. Carsey
language : en
Publisher: SAGE Publications
Release Date : 2013-08-05
Monte Carlo Simulation And Resampling Methods For Social Science written by Thomas M. Carsey and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-05 with Social Science categories.
Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.