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R High Performance Programming

R High Performance Programming

By : Aloysius Shao Qin Lim, Tjhi W Chandra
4.4 (14)
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R High Performance Programming

R High Performance Programming

4.4 (14)
By: Aloysius Shao Qin Lim, Tjhi W Chandra

Overview of this book

This book is for programmers and developers who want to improve the performance of their R programs by making them run faster with large data sets or who are trying to solve a pesky performance problem.
Table of Contents (12 chapters)
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11
Index

Use of built-in functions


As a programming language, R comes with low-level operators, such as basic arithmetic operators that can be used to construct more complex operators or functions. While R provides the flexibility to define functions, a performance comparison between an R function versus an equivalent function in a compiled language would almost always favor the latter. However, R and some CRAN packages provide a rich set of functions that are implemented in compiled languages such as C/C++. It is usually preferable to use these functions rather than to write custom R functions to perform the same task.

Consider a simple example of how to calculate the sums of the rows of the following random matrix data. A code to perform these functions can be constructed by calling the apply() function, and setting the margin to 1 (representing a row operation) and by setting the FUN (or function) argument to sum. Alternatively, R provides a built-in function for this purpose called rowSums. The...

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