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Author : Enno Mammen
Publisher : Springer Science & Business Media
ISBN 13 : 1461229502
Total Pages : 205 pages
Book Rating : 4.4/5 (612 download)
Download or read book When Does Bootstrap Work? written by Enno Mammen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Enno Mammen
Publisher : Springer
ISBN 13 : 9780387978673
Total Pages : 0 pages
Book Rating : 4.9/5 (786 download)
Download or read book When Does Bootstrap Work? written by Enno Mammen and published by Springer. This book was released on 1992-07-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In these notes some results are presented for the asymptotic behavior of the bootstrap procedure. Bootstrap is a procedure for estimating (approximating) the distribution of a statistic. It is based on resampling and simulations. It was been introduced in Efron (1979) and in the last decade it has been discussed for a wide variety of statistical problems. Introductory are the articles Efron and Gong (1983) and Efron and Tibshirani (1986) and the book Helmers (1991b). Many applications of bootstrap are discussed in Efron (1982). Survey articles are Beran (1984b), Hinkley (1988), and Diciccio and Romano (1988a). For many classical decision problems (testing and estimation problems, prediction, construction of confidence regions) bootstrap has been compared with classical approximations based on mathematical limit theorems and expansions (for instance normal approximations, empirical Edgeworth expansions) (see for instance Bretagnolle (1983) and Beran (1982, 1984a, 1987, 1988), Abramovitch and Singh (1985), and Hall (1986a, 1988) ). An asymptotic treatment of bootstrap is contained in the book Beran and Ducharme (1991). A detailed analysis of bootstrap based on higher order Edgeworth expansions has been carried out in the book Hall (1992). Recent publications on bootstrap can also be found in the conference volumes LePage and Billard (1992) and Joeckel, Rothe, and Sendler (1992). We will consider the application of bootstrap in three contexts : estimation of smooth functionals, nonparametric curve estimation, and linear models. We do not attempt a complete description of bootstrap in these areas.
Author : Enno Mammen
Publisher :
ISBN 13 : 9781461229513
Total Pages : 212 pages
Book Rating : 4.2/5 (295 download)
Download or read book When Does Bootstrap Work? written by Enno Mammen and published by . This book was released on 1992-07-29 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Bradley Efron
Publisher : CRC Press
ISBN 13 : 9780412042317
Total Pages : 456 pages
Book Rating : 4.0/5 (423 download)
Download or read book An Introduction to the Bootstrap written by Bradley Efron and published by CRC Press. This book was released on 1994-05-15 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.
Author : Humberto Barreto
Publisher : Cambridge University Press
ISBN 13 : 9780521843195
Total Pages : 810 pages
Book Rating : 4.8/5 (431 download)
Download or read book Introductory Econometrics written by Humberto Barreto and published by Cambridge University Press. This book was released on 2006 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics.
Author : Michael R. Chernick
Publisher : John Wiley & Sons
ISBN 13 : 1118211596
Total Pages : 337 pages
Book Rating : 4.1/5 (182 download)
Download or read book Bootstrap Methods written by Michael R. Chernick and published by John Wiley & Sons. This book was released on 2011-09-23 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical and accessible introduction to the bootstrap method——newly revised and updated Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics. Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features: The addition of a second, extended bibliography devoted solely to publications from 1999–2007, which is a valuable collection of references on the latest research in the field A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials A revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacks Added coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing data New examples and illustrations as well as extensive historical notes at the end of each chapter With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.
Author : A. C. Davison
Publisher : Cambridge University Press
ISBN 13 : 9780521574716
Total Pages : 606 pages
Book Rating : 4.5/5 (747 download)
Download or read book Bootstrap Methods and Their Application written by A. C. Davison and published by Cambridge University Press. This book was released on 1997-10-28 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: Disk contains the library functions and documentation for use with Splus for Windows.
Author : Michael R. Chernick
Publisher : John Wiley & Sons
ISBN 13 : 1118625412
Total Pages : 318 pages
Book Rating : 4.1/5 (186 download)
Download or read book An Introduction to Bootstrap Methods with Applications to R written by Michael R. Chernick and published by John Wiley & Sons. This book was released on 2014-08-21 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to bootstrap methods in the R programming environment Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the practicality of this approach and successfully utilizes R to illustrate applications for the bootstrap and other resampling methods. This book provides a modern introduction to bootstrap methods for readers who do not have an extensive background in advanced mathematics. Emphasis throughout is on the use of bootstrap methods as an exploratory tool, including its value in variable selection and other modeling environments. The authors begin with a description of bootstrap methods and its relationship to other resampling methods, along with an overview of the wide variety of applications of the approach. Subsequent chapters offer coverage of improved confidence set estimation, estimation of error rates in discriminant analysis, and applications to a wide variety of hypothesis testing and estimation problems, including pharmaceutical, genomics, and economics. To inform readers on the limitations of the method, the book also exhibits counterexamples to the consistency of bootstrap methods. An introduction to R programming provides the needed preparation to work with the numerous exercises and applications presented throughout the book. A related website houses the book's R subroutines, and an extensive listing of references provides resources for further study. Discussing the topic at a remarkably practical and accessible level, An Introduction to Bootstrap Methods with Applications to R is an excellent book for introductory courses on bootstrap and resampling methods at the upper-undergraduate and graduate levels. It also serves as an insightful reference for practitioners working with data in engineering, medicine, and the social sciences who would like to acquire a basic understanding of bootstrap methods.
Author : S. N. Lahiri
Publisher : Springer Science & Business Media
ISBN 13 : 147573803X
Total Pages : 382 pages
Book Rating : 4.4/5 (757 download)
Download or read book Resampling Methods for Dependent Data written by S. N. Lahiri and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : John Fox
Publisher : SAGE Publications
ISBN 13 : 1483321312
Total Pages : 612 pages
Book Rating : 4.4/5 (833 download)
Download or read book Applied Regression Analysis and Generalized Linear Models written by John Fox and published by SAGE Publications. This book was released on 2015-03-18 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website. NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website.
Author : Kenichi Shimizu
Publisher : Springer Science & Business Media
ISBN 13 : 3834897787
Total Pages : 137 pages
Book Rating : 4.8/5 (348 download)
Download or read book Bootstrapping Stationary ARMA-GARCH Models written by Kenichi Shimizu and published by Springer Science & Business Media. This book was released on 2010-11-01 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bootstrap technique is a useful tool for assessing uncertainty in statistical estimation and thus it is widely applied for risk management. Bootstrap is without doubt a promising technique, however, it is not applicable to all time series models. A wrong application could lead to a false decision to take too much risk. Kenichi Shimizu investigates the limit of the two standard bootstrap techniques, the residual and the wild bootstrap, when these are applied to the conditionally heteroscedastic models, such as the ARCH and GARCH models. The author shows that the wild bootstrap usually does not work well when one estimates conditional heteroscedasticity of Engle’s ARCH or Bollerslev’s GARCH models while the residual bootstrap works without problems. Simulation studies from the application of the proposed bootstrap methods are demonstrated together with the theoretical investigation.
Author : Rich Christiansen
Publisher :
ISBN 13 : 9781932226720
Total Pages : 0 pages
Book Rating : 4.2/5 (267 download)
Download or read book Bootstrap Business written by Rich Christiansen and published by . This book was released on 2009-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is one of the most practical, sound and wise investments you will ever make in your small business. It explains Rich & Ron's process to take a $5,000 investment and bootstrap a successful company. Build a business from where you are. Avoid the big mistakes that kill most businesses. Secure your future financially while maintaining a balanced lifestyle. Bootstrap Business is a self-contained book that explores Rich & Ron's experiences in launching companies. 28 attempts, 10 miserable failures, 8 multi-million dollar successes. Hard work is required. You can do it. Bootstrap Business teaches you how.
Author : Gareth James
Publisher : Springer Nature
ISBN 13 : 3031387473
Total Pages : 617 pages
Book Rating : 4.0/5 (313 download)
Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Author : Bradley Efron
Publisher : SIAM
ISBN 13 : 9781611970319
Total Pages : 99 pages
Book Rating : 4.9/5 (73 download)
Download or read book The Jackknife, the Bootstrap, and Other Resampling Plans written by Bradley Efron and published by SIAM. This book was released on 1982-01-01 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: The jackknife and the bootstrap are nonparametric methods for assessing the errors in a statistical estimation problem. They provide several advantages over the traditional parametric approach: the methods are easy to describe and they apply to arbitrarily complicated situations; distribution assumptions, such as normality, are never made. This monograph connects the jackknife, the bootstrap, and many other related ideas such as cross-validation, random subsampling, and balanced repeated replications into a unified exposition. The theoretical development is at an easy mathematical level and is supplemented by a large number of numerical examples. The methods described in this monograph form a useful set of tools for the applied statistician. They are particularly useful in problem areas where complicated data structures are common, for example, in censoring, missing data, and highly multivariate situations.
Author : Rand R. Wilcox
Publisher : Academic Press
ISBN 13 : 0123869838
Total Pages : 713 pages
Book Rating : 4.1/5 (238 download)
Download or read book Introduction to Robust Estimation and Hypothesis Testing written by Rand R. Wilcox and published by Academic Press. This book was released on 2012-01-12 with total page 713 pages. 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"--
Author : Andrew S. Zieffler
Publisher : John Wiley & Sons
ISBN 13 : 1118063678
Total Pages : 286 pages
Book Rating : 4.1/5 (18 download)
Download or read book Comparing Groups written by Andrew S. Zieffler and published by John Wiley & Sons. This book was released on 2012-01-10 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on guide to using R to carry out key statistical practices in educational and behavioral sciences research Computing has become an essential part of the day-to-day practice of statistical work, broadening the types of questions that can now be addressed by research scientists applying newly derived data analytic techniques. Comparing Groups: Randomization and Bootstrap Methods Using R emphasizes the direct link between scientific research questions and data analysis. Rather than relying on mathematical calculations, this book focus on conceptual explanations and the use of statistical computing in an effort to guide readers through the integration of design, statistical methodology, and computation to answer specific research questions regarding group differences. Utilizing the widely-used, freely accessible R software, the authors introduce a modern approach to promote methods that provide a more complete understanding of statistical concepts. Following an introduction to R, each chapter is driven by a research question, and empirical data analysis is used to provide answers to that question. These examples are data-driven inquiries that promote interaction between statistical methods and ideas and computer application. Computer code and output are interwoven in the book to illustrate exactly how each analysis is carried out and how output is interpreted. Additional topical coverage includes: Data exploration of one variable and multivariate data Comparing two groups and many groups Permutation tests, randomization tests, and the independent samples t-Test Bootstrap tests and bootstrap intervals Interval estimates and effect sizes Throughout the book, the authors incorporate data from real-world research studies as well aschapter problems that provide a platform to perform data analyses. A related Web site features a complete collection of the book's datasets along with the accompanying codebooks and the R script files and commands, allowing readers to reproduce the presented output and plots. Comparing Groups: Randomization and Bootstrap Methods Using R is an excellent book for upper-undergraduate and graduate level courses on statistical methods, particularlyin the educational and behavioral sciences. The book also serves as a valuable resource for researchers who need a practical guide to modern data analytic and computational methods.
Author : DŽborah Berman Santana
Publisher : University of Arizona Press
ISBN 13 : 9780816515912
Total Pages : 228 pages
Book Rating : 4.5/5 (159 download)
Download or read book Kicking Off the Bootstraps written by DŽborah Berman Santana and published by University of Arizona Press. This book was released on 1996 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: While small communities in Third World countries usually seem at the mercy of central governments and foreign capitalists, local activists can help exploited peoples correct environmental abuses and social injustices and seize control of their own destinies. Kicking Off the Bootstraps is a powerful case history of such an effort. It describes a grassroots activist movement that emerged in the Puerto Rican community of Salinas to counter the poverty and economic dependence experienced by its citizens in the wake of "Operation Bootstrap," a post-World War II industrial development program. DŽborah Berman Santana examines the efforts of the community to develop its own economic strategy based primarily on environmentally and socially responsible uses of local natural and human resources. Berman Santana shows how local activists are seeking to empower the Salinas community to make decisions concerning economic development. She evaluates present-day efforts to develop positive alternatives, examining the motivations of the activists, the nature of their projects, their efforts to mobilize the community, their dealings with government and other organizations, and the obstacles they face. In a closing chapter, she addresses the potential roles of community leaders, outside activists, local businesses, and government in actualizing these alternatives. A testimony to one community's efforts to determine its own future, Kicking Off the Bootstraps deals with real issues such as control over productive resources, quality of life, and environmental health. It also extends an examination of community-directed activism to an exploration of policy implications for sustainable development. While this concept is often too vague to be applied to real strategies, the Salinas experience provides a clear idea of what sustainable development can--and should--mean in actual practice.
