An Introduction To Bootstrap Methods With Applications To R
DOWNLOAD
Download An Introduction To Bootstrap Methods With Applications To R PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get An Introduction To Bootstrap Methods With Applications To R book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Bootstrap Methods
DOWNLOAD
Author : Gerhard Dikta
language : en
Publisher: Springer Nature
Release Date : 2021-08-10
Bootstrap Methods written by Gerhard Dikta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-10 with Mathematics categories.
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.
An Introduction To Bootstrap Methods With Applications To R
DOWNLOAD
Author : Michael R. Chernick
language : en
Publisher: John Wiley & Sons
Release Date : 2014-08-21
An Introduction To Bootstrap Methods With Applications To R written by Michael R. Chernick 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 2014-08-21 with Mathematics categories.
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.
Bootstrap Methods And Their Application
DOWNLOAD
Author : A. C. Davison
language : en
Publisher: Cambridge University Press
Release Date : 1997-10-28
Bootstrap Methods And Their Application written by A. C. Davison and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-10-28 with Computers categories.
Disk contains the library functions and documentation for use with Splus for Windows.
Bootstrap Methods
DOWNLOAD
Author : Michael R. Chernick
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-23
Bootstrap Methods written by Michael R. Chernick 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 2011-09-23 with Mathematics categories.
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.
An Introduction To The Bootstrap
DOWNLOAD
Author : Bradley Efron
language : en
Publisher: CRC Press
Release Date : 1994-05-15
An Introduction To The Bootstrap written by Bradley Efron and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-05-15 with Mathematics categories.
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.
Comparing Groups
DOWNLOAD
Author : Andrew S. Zieffler
language : en
Publisher: John Wiley & Sons
Release Date : 2012-01-10
Comparing Groups written by Andrew S. Zieffler 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 2012-01-10 with Social Science categories.
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.
An Introduction To Statistical Learning
DOWNLOAD
Author : Gareth James
language : en
Publisher: Springer Nature
Release Date : 2023-06-30
An Introduction To Statistical Learning written by Gareth James and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Mathematics categories.
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.
Bootstrapping
DOWNLOAD
Author : Christopher Z. Mooney
language : en
Publisher: SAGE
Release Date : 1993-08-09
Bootstrapping written by Christopher Z. Mooney and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-08-09 with Philosophy categories.
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.
Ranked Set Sampling
DOWNLOAD
Author : Munir Ahmad
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2010-09-13
Ranked Set Sampling written by Munir Ahmad and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-13 with Social Science categories.
Ranked Set Sampling is one of the new areas of study in this region of the world and is a growing subject of research. Recently, researchers have paid attention to the development of the types of sampling; though it was not welcome in the beginning, it has numerous advantages over the classical sampling techniques. Ranked Set Sampling is doubly random and can be used in any survey designs. The Pakistan Journal of Statistics had attracted statisticians and samplers around the world to write up aspects of Ranked Set Sampling. All of the essays in this book have been reviewed by many critics. This volume can be used as a reference book for postgraduate students in economics, social sciences, medical and biological sciences, and statistics. The subject is still a hot topic for MPhil and PhD students for their dissertations.
Probability And Statistics With R
DOWNLOAD
Author : Maria Dolores Ugarte
language : en
Publisher: CRC Press
Release Date : 2008-04-11
Probability And Statistics With R written by Maria Dolores Ugarte and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-11 with Mathematics categories.
Designed for an intermediate undergraduate course, Probability and Statistics with R shows students how to solve various statistical problems using both parametric and nonparametric techniques via the open source software R. It provides numerous real-world examples, carefully explained proofs, end-of-chapter problems, and illuminating graphs