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. The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. 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, The Art of R Programming is your guide to harnessing the power of statistical computing.
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis.
After finishing this book, you will be well equipped to start applying machine learning techniques to your own datasets.
Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to ...
R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved.
The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.
Become an efficient data scientist with R About This Book Explore the R language from basic types and data structures to advanced topics Learn how to tackle programming problems and explore both functional and object-oriented programming ...
This abstract state Step"(I ) is sound: it subsumes all the states after i transitions from an initial state implied by I. This soundness of i consecutive applications of Step" is clear because each step by Step" over-approximates the ...
or one-tailed test ("two.side", "less", or "greater"), and method specifies the type of correlation ("pearson", "kendall", or "spearman") to compute. Use alternative ="less" when the research hypothesis is that the population ...
You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory ...
Cox, D. R. and Oakes, D. (1984), Analysis of Survival Data, Chapman & Hall, London. Everitt, B. S. (1994), A Handbook of Statistical Analyses Using S-PLUS, Chapman & Hall, London. Hájek, J., Šidák, Z., and Sen, P. K. (1999), ...