Generalized Additive Models: An Introduction with R, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation.
Generalized Additive Models: An Introduction with R, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
Numéro d'article: 105372836

Generalized Additive Models: An Introduction with R, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

Numéro d'article: 105372836

XPF 22584

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The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation.
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Ce qui se démarque

Comprehensive Guide
This book offers a thorough introduction to Generalized Additive Models (GAMs), making complex statistical concepts accessible for beginners and practitioners alike, enhancing analytical skills and decision-making.
Practical R Examples
Packed with practical R coding examples, the text bridges theory and application, allowing readers to implement GAMs effectively in real-world data analysis scenarios, ensuring a hands-on learning experience.
Updated Content
The second edition features updated methodologies and expanded topics, reflecting the latest advancements in statistical science, ensuring that readers are equipped with current knowledge and techniques in GAMs.

Détails du produit

Shop Generalized Additive Models: An Introduction with R, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) online at a best price in French Polynesia. 1498728332
Publisher Chapman and Hall/CRC
Publication date 30 May 2017
Edition 2nd
Language English
Print length 496 pages
ISBN-10 1498728332
ISBN-13 978-1498728331
Item weight 1.05 kg
Dimensions 15.6 x 2.69 x 23.39 cm

À qui est-ce destiné ?

Suitable For
  • Data Scientists

    Ideal for data scientists seeking to use generalized additive models for complex data visualization and analysis.

  • Graduate Students

    Beneficial for graduate students studying statistics or data science looking to deepen their understanding of modeling techniques.

  • Statisticians

    Great for professional statisticians needing a comprehensive guide to generalized additive models and their applications.

Not Suitable For
  • Beginners

    May not be suitable for beginners lacking basic statistical knowledge or experience with R programming.

DESCRIPTION DU PRODUIT

Generalized Additive Models: An Introduction with R, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

About This Item

Introducing the "Generalized Additive Models: An Introduction with R, Second Edition" - your comprehensive guide to mastering generalized additive models using R programming! Whether you're a beginner or an experienced statistician, this textbook is a must-have for anyone interested in delving into the world of statistical modeling and analysis in R. Packed with practical examples and step-by-step instructions, this book will equip you with the skills and knowledge necessary to confidently apply generalized additive models to your data analysis projects. With the second edition of this popular Chapman & HallCRC Texts in Statistical Science series, you'll explore the foundation and theory behind additive models, along with their implementation in the R programming language. The book offers a systematic and accessible approach, making it suitable for students, professionals, and researchers alike. Through clear explanations and real-world examples, you'll learn how to leverage the power of R packages to perform regression analysis, manipulate data, and create visually appealing graphics.

Whether you're analyzing survey data, conducting social network analysis, or predicting sales trends, this book will guide you through the entire process. Key features of "Generalized Additive Models: An Introduction with R, Second Edition": 1. Comprehensive Coverage: From the basics of statistical modeling to advanced topics like smoothing and model selection, this book covers it all. Gain a deep understanding of generalized additive models and their practical applications. 2.

Hands-on Examples: Learn by doing with numerous examples and exercises throughout the book. Apply what you've learned to real-world scenarios to solidify your understanding and develop your skills. 3. R Programming: Master the R programming language and take advantage of its powerful statistical analysis and data manipulation capabilities.

Enhance your data analysis workflow and produce high-quality visualizations with ease. 4. Practical Tips and Tricks: Benefit from the author's expertise as they share practical tips and tricks for successful model building and interpretation. Avoid common pitfalls and optimize your modeling techniques. 5.

Updated Second Edition: This revised edition includes updated content, additional examples, and revised exercises to ensure you have the most up-to-date knowledge and skills in the field of generalized additive models. Unlock the power of statistical modeling in R with the "Generalized Additive Models: An Introduction with R, Second Edition." Take your data analysis and statistical modeling skills to the next level and gain a competitive edge in your field. Order your copy today and embark on a journey of mastering regression models, statistical modeling, and more using the R programming language!.

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Higher Education Editorial Review

Generalized Additive Models An Introduction With R, Second Edition Chapman & Hall/CRC Texts In Statistical Science offers a comprehensive exploration of additive models, ideal for statisticians and data scientists seeking advanced statistical approaches. Published by Chapman and Hall/CRC on 30 May 2017, this second edition encompasses 496 pages filled with practical insights and clear R programming examples, making it easily accessible for readers. With its emphasis on clarity of explanations, many users appreciate how the text breaks down complex concepts, allowing for effective learning and application. This updated edition includes new topics and chapters that enhance the understanding of generalized additive models, which many readers find beneficial.

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Avantages

  • Comprehensive exploration of additive models
  • Practical insights with clear R examples
  • Easily accessible for statisticians and data scientists
  • Includes new topics and chapters
  • Clear explanations of complex concepts

Les inconvénients

  • Some readers may prefer a more concise format

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