Robust Statistical Methods with R, Second Edition

The second edition of "Robust Statistical Methods with R" is a comprehensive guide to robust procedures,with an emphasis on new developments and computational aspects. It covers a wide range of robust methods,including sequential estimators,multivariate models,and measurement error models. The book is designed for researchers and postgraduate students in statistics and mathematics and will be an invaluable resource for anyone working with robust data analysis.

\n Format: Hardback
\n Length: 254 pages
\n Publication date: 20 May 2019
\n Publisher: Taylor & Francis Ltd
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The second edition of "Robust Statistical Methods with R" is a comprehensive and up-to-date resource for practitioners and researchers in the field of statistics. This book offers a systematic treatment of robust procedures, with a particular emphasis on new developments and computational aspects.

The book begins with an introduction to robust statistics, providing a clear overview of the principles and applications. It then delves into the theoretical foundations of robust methods, covering topics such as robust estimation, hypothesis testing, and confidence intervals.

One of the key strengths of this edition is its extensive coverage of numerical examples and notes on the R environment. The authors have provided numerous code snippets and exercises to help readers understand and apply the robust methods discussed in the book. Additionally, the updated chapter on the multivariate model contains additional material on the visualization of multivariate data in R, making it a valuable resource for researchers working with complex data sets.

Another notable feature of the book is its focus on robust procedures in measurement error models. The authors have dedicated a new chapter to this topic, which concentrates mainly on the rank procedures. Rank procedures are less sensitive to errors than other procedures, making them particularly useful in situations where data are contaminated with measurement errors. The chapter provides a detailed explanation of rank procedures, including their properties, assumptions, and applications.

Throughout the book, the authors emphasize the computational aspects of robust statistics. They provide detailed explanations of the R software and its functions, and offer the own procedures of the authors in the R software on the book's website. This makes the book an invaluable resource for researchers and postgraduate students who want to learn and apply robust statistical methods using R.

In conclusion, the second edition of "Robust Statistical Methods with R" is a comprehensive and practical guide to robust statistical methods. It offers a rigorous treatment of the whole range of robust methods, with a particular emphasis on new developments and computational aspects. The book's extensive coverage of numerical examples, notes on the R environment, and focus on robust procedures in measurement error models make it an invaluable resource for researchers and postgraduate students in statistics and mathematics. Whether you are a novice or an experienced practitioner, this book will help you improve your statistical analysis and make more robust and reliable conclusions.

\n Weight: 546g\n
Dimension: 164 x 243 x 17 (mm)\n
ISBN-13: 9781138035362\n
Edition number: 2 New edition\n