- Download Chapter 3: "Matrices and Arrays"
- Download the code from the book
- Download the data files from the book
R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.
Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: - Create artful graphs to visualize complex data sets and functions
- Write more efficient code using parallel R and vectorization
- Interface R with C/C++ and Python for increased speed or functionality
- Find new R packages for text analysis, image manipulation, and more
- Squash annoying bugs with advanced debugging techniques
Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, ## About the Author
## Table of Contents
View the detailed Table of Contents (PDF) View the Index (PDF) (top)## Reviews"If a person really wants to be able to speak the R language and become a competent R programmer then . . . one can find no better guide than Norman Matloff's "The book I'd recommend for someone wanting to learn R, especially for someone with more experience in programming than statistics." "Good from cover to cover. Enough depth that the experienced R user will find useful things in the later chapters." “If you are serious about learning R . . . "Makes it look easy for those scientists who need to make numerical models based on statistical analysis. Serious stuff for people who are already R programmers, but it has a lot of value for entry level folks too." "If you need to do statistical work as a programmer I highly recommend buying it." "An R programming book that starts from the beginning. If you have at least a vague idea of what programming is, you should find |
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