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Author | : Philippe Barbe |
Publisher | : Springer Science & Business Media |
Total Pages | : 236 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461225329 |
Download The Weighted Bootstrap Book in PDF, ePub and Kindle
INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X of Xl ' n independent and identically distributed H.i.d.) random variables (r. v,'s) with unknown probability measure (p.m.) P . Assume we are interested in approximating the distribution of a statistical functional T(P ) the -1 nn empirical counterpart of the functional T(P) , where P n := n l:i=l aX. is 1 the empirical p.m. Since in some sense P is close to P when n is large, n • • LLd. from P and builds the empirical p.m. if one samples Xl ' ... , Xm n n -1 mn • • P T(P ) conditionally on := mn l: i =1 a • ' then the behaviour of P m n,m n n n X. 1 T(P ) should imitate that of when n and mn get large. n This idea has lead to considerable investigations to see when it is correct, and when it is not. When it is not, one looks if there is any way to adapt it.
Author | : Philippe Barbe |
Publisher | : |
Total Pages | : 244 |
Release | : 1995-02-24 |
Genre | : |
ISBN | : 9781461225331 |
Download The Weighted Bootstrap Book in PDF, ePub and Kindle
Author | : Peter Hall |
Publisher | : Springer Science & Business Media |
Total Pages | : 359 |
Release | : 2013-12-01 |
Genre | : Mathematics |
ISBN | : 146124384X |
Download The Bootstrap and Edgeworth Expansion Book in PDF, ePub and Kindle
This monograph addresses two quite different topics, each being able to shed light on the other. Firstly, it lays the foundation for a particular view of the bootstrap. Secondly, it gives an account of Edgeworth expansion. The first two chapters deal with the bootstrap and Edgeworth expansion respectively, while chapters 3 and 4 bring these two themes together, using Edgeworth expansion to explore and develop the properties of the bootstrap. The book is aimed at graduate level for those with some exposure to the methods of theoretical statistics. However, technical details are delayed until the last chapter such that mathematically able readers without knowledge of the rigorous theory of probability will have no trouble understanding most of the book.
Author | : Gerhard Dikta |
Publisher | : Springer Nature |
Total Pages | : 256 |
Release | : 2021-08-10 |
Genre | : Mathematics |
ISBN | : 3030734803 |
Download Bootstrap Methods Book in PDF, ePub and Kindle
This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time. The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.
Author | : Bradley Efron |
Publisher | : CRC Press |
Total Pages | : 456 |
Release | : 1994-05-15 |
Genre | : Mathematics |
ISBN | : 9780412042317 |
Download An Introduction to the Bootstrap Book in PDF, ePub and Kindle
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 | : John Fox |
Publisher | : SAGE Publications |
Total Pages | : 612 |
Release | : 2015-03-18 |
Genre | : Social Science |
ISBN | : 1483321312 |
Download Applied Regression Analysis and Generalized Linear Models Book in PDF, ePub and Kindle
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 | : A. C. Davison |
Publisher | : Cambridge University Press |
Total Pages | : 606 |
Release | : 1997-10-28 |
Genre | : Computers |
ISBN | : 9780521574716 |
Download Bootstrap Methods and Their Application Book in PDF, ePub and Kindle
Disk contains the library functions and documentation for use with Splus for Windows.
Author | : Christopher Z. Mooney |
Publisher | : SAGE |
Total Pages | : 84 |
Release | : 1993-08-09 |
Genre | : Philosophy |
ISBN | : 9780803953819 |
Download Bootstrapping Book in PDF, ePub and Kindle
"This book is. . . clear and well-written. . . anyone with any interest in the basis of quantitative analysis simply must read this book. . . . well-written, with a wealth of explanation. . ." --Dougal Hutchison in Educational Research Using real data examples, this volume shows how to apply bootstrapping when the underlying sampling distribution of a statistic cannot be assumed normal, as well as when the sampling distribution has no analytic solution. In addition, it discusses the advantages and limitations of four bootstrap confidence interval methods--normal approximation, percentile, bias-corrected percentile, and percentile-t. The book concludes with a convenient summary of how to apply this computer-intensive methodology using various available software packages.
Author | : Michael R. Chernick |
Publisher | : John Wiley & Sons |
Total Pages | : 337 |
Release | : 2011-09-23 |
Genre | : Mathematics |
ISBN | : 1118211596 |
Download Bootstrap Methods Book in PDF, ePub and Kindle
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 | : Abdelhak M. Zoubir |
Publisher | : Cambridge University Press |
Total Pages | : 238 |
Release | : 2004-05-06 |
Genre | : Technology & Engineering |
ISBN | : 9781139452021 |
Download Bootstrap Techniques for Signal Processing Book in PDF, ePub and Kindle
The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.