Statistical Computing in C++ and R

Statistical Computing in C++ and R focuses on code development in C++ and R, emphasizing their distinct features and their use in tandem for code writing beyond what can be obtained from either language alone. It covers object-oriented languages, boot-camp, optimization, numerical linear algebra, random number generation, abstract data structures, and parallel computing concepts. The book includes numerous student exercises and provides downloadable programs. It lays the foundation for original code development in a research environment.

Format: Paperback / softback
Length: 556 pages
Publication date: 21 January 2023
Publisher: Taylor & Francis Ltd

The field of statistical methodology has undergone a remarkable transformation with the integration of advanced computational techniques. This convergence has necessitated the development of new methodological ideas that require translation into practical code and subsequent numerical evaluation against competing procedures. In response to this challenge, Statistical Computing in C++ and R emerges as a valuable resource. This book focuses specifically on the art of code writing, emphasizing the development and utilization of these symbiotic languages in conjunction. It highlights the distinct features offered by C++ and R, which, when combined, enable code writing to surpass the capabilities of either language alone.

The text begins with an introduction to object-oriented languages, providing a foundational understanding for subsequent chapters. It then transitions into a boot-camp-style tutorial, guiding students through the practical application of C++ and R. The authors proceed to discuss code development for solving a range of computational problems relevant to statistics, such as optimization, numerical linear algebra, and random number generation. Later chapters delve into abstract data structures (ADTs) and parallel computing concepts, expanding the scope of statistical computing techniques.

To enhance the learning experience, the book includes numerous student exercises spanning different levels of difficulty. These exercises not only reinforce the theoretical concepts but also encourage hands-on practice and problem-solving skills. Furthermore, the text integrates both C++ and R, enabling students to leverage the strengths of each language for the solution of statistical computing problems. It showcases the seamless interoperability between C++ code in R and R functions in C++ programs, promoting a holistic approach to statistical analysis.

To support the learning process, the authors have made downloadable programs available on their website. These programs serve as practical examples and allow students to apply the concepts learned in the book directly to their own computing endeavors.

In conclusion, Statistical Computing in C++ and R is a comprehensive guide that empowers students and practitioners to excel in the field of statistical computing. By emphasizing code writing, integrating C++ and R, and covering a wide range of computational problems, this book equips readers with the skills and knowledge necessary to tackle complex statistical analyses and make meaningful contributions to the field.

Weight: 1030g
Dimension: 254 x 178 (mm)
ISBN-13: 9781032477619