This comprehensive compendium of algorithms and data structures covers many theoretical issues from a practical perspective. Chapters include information on finite precision issues as well as discussions on specific algorithms where algorithmic techniques are of special importance - for example, algorithms for drawing graphs, algorithms for...
An Introduction to Partial Differential Equations with MATLAB®, Second Edition illustrates the usefulness of PDEs through numerous applications and helps students appreciate the beauty of the underlying mathematics. Updated throughout, this second edition of a bestseller shows students how PDEs can...
Based on the author’s introductory course at the University of Oregon, Explorations in Computing: An Introduction to Computer Science focuses on the fundamental idea of computation and offers insight into how computation is used to solve a variety of interesting and important real-world problems. Taking an...
Mike Driscoll takes you on a journey talking to a hall-of-fame list of truly remarkable Python experts. You'll be inspired every time by their passion for the Python language, as they share with you their experiences, contributions, and careers in Python.
In recent years the subject of computer programming has been recognized as a discipline whose mastery
is fundamental and crucial to the success of many engineering projects and which is amenable to
scientific treatement and presentation. It has advanced from a craft to an academic discipline. The initial
outstanding contributions...
With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples. Keeping mathematical details to a minimum, the book covers key topics, including both discrete and continuous time data, parametric proportional...
This introduction to numerical analysis shows how the mathematics of calculus and linear algebra are implemented in computer algorithms. It develops a deep understanding of why numerical methods work and exactly what their limitations are....
With its flexible capabilities and open-source platform, R has become a major tool for analyzing detailed, high-quality baseball data. Analyzing Baseball Data with R provides an introduction to R for sabermetricians, baseball enthusiasts, and students interested in exploring the rich sources of baseball data. It...
Developed by Jean-Paul Benzérci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its...
Information retrieval is a sub-field of computer science that deals with the automated storage and retrieval of documents. Providing the latest information retrieval techniques, this guide discusses Information Retrieval data structures and algorithms, including implementations in C. Aimed at software engineers building systems with...
As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of ABC methods. These simple, but...
R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications,...
