Permutation Tests

Permutation Tests PDF Author: Phillip Good
Publisher: Springer Science & Business Media
ISBN: 1475723466
Category : Mathematics
Languages : en
Pages : 238

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Book Description
A step-by-step guide to the application of permutation tests in biology, medicine, science, and engineering. The intuitive and informal style makes this manual ideally suitable for students and researchers approaching these methods for the first time. In particular, it shows how to handle the problems of missing and censored data, nonresponders, after-the-fact covariates, and outliers.

Permutation Tests

Permutation Tests PDF Author: Phillip Good
Publisher: Springer Science & Business Media
ISBN: 1475723466
Category : Mathematics
Languages : en
Pages : 238

Get Book Here

Book Description
A step-by-step guide to the application of permutation tests in biology, medicine, science, and engineering. The intuitive and informal style makes this manual ideally suitable for students and researchers approaching these methods for the first time. In particular, it shows how to handle the problems of missing and censored data, nonresponders, after-the-fact covariates, and outliers.

An Introduction to Statistical Learning

An Introduction to Statistical Learning PDF Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617

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Book Description
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.

Resampling-Based Multiple Testing

Resampling-Based Multiple Testing PDF Author: Peter H. Westfall
Publisher: John Wiley & Sons
ISBN: 9780471557616
Category : Mathematics
Languages : en
Pages : 382

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Book Description
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 Robust Estimation and Hypothesis Testing

Introduction to Robust Estimation and Hypothesis Testing PDF Author: Rand R. Wilcox
Publisher: Academic Press
ISBN: 0123869838
Category : Mathematics
Languages : en
Pages : 713

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Book Description
"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"--

Permutation, Parametric, and Bootstrap Tests of Hypotheses

Permutation, Parametric, and Bootstrap Tests of Hypotheses PDF Author: Phillip I. Good
Publisher: Springer Science & Business Media
ISBN: 0387271589
Category : Mathematics
Languages : en
Pages : 331

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Book Description
Previous edition sold over 1400 copies worldwide. This new edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises.

Bootstrap Methods

Bootstrap Methods PDF Author: Michael R. Chernick
Publisher: John Wiley & Sons
ISBN: 1118211596
Category : Mathematics
Languages : en
Pages : 337

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Book Description
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.

The Practice of Business Statistics Companion Chapter 18: Bootstrap Methods and Permutation Tests

The Practice of Business Statistics Companion Chapter 18: Bootstrap Methods and Permutation Tests PDF Author: David S. Moore
Publisher: W. H. Freeman
ISBN: 9780716757269
Category : Business & Economics
Languages : en
Pages : 74

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Book Description


An Introduction to the Bootstrap

An Introduction to the Bootstrap PDF Author: Bradley Efron
Publisher: CRC Press
ISBN: 9780412042317
Category : Mathematics
Languages : en
Pages : 456

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Book Description
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.

Bootstrap Methods and Their Application

Bootstrap Methods and Their Application PDF Author: A. C. Davison
Publisher: Cambridge University Press
ISBN: 9780521574716
Category : Computers
Languages : en
Pages : 606

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Book Description
Disk contains the library functions and documentation for use with Splus for Windows.

Bootstrapping

Bootstrapping PDF Author: Christopher Z. Mooney
Publisher: SAGE
ISBN: 9780803953819
Category : Philosophy
Languages : en
Pages : 84

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Book Description
"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.