Guide to a high-performance, powerful R installation

R is an amazing language with 25 years of development behind it, but you can make the most from R with additional components. An IDE makes developing in R more convenient; packages extend R's capabilities; and multi-threaded libraries make computations faster. 

Since these additional components aren't included on the official R website, getting the ideal R environment set up can be a bit tricky. Fortunately, there's a handy R installation guide by Mauricio Vargas that explains how to get everything you need set up on Windows, Mac and Ubuntu Linux. On each platform, the guide describes how to install:

• The R language engine
• The RStudio IDE.
• The tidyverse suite of packages
• Multi-threaded math libraries (BLAS). On Windows, Mauricio recommends Microsoft R Open ("what made my R and Windows experience amazing"). For Mac and Unix he suggests installing OpenBLAS, but I'll add that Microsoft R Open provides BLAS acceleration on those platforms as well. It's easy to configure RStudio to use Microsoft R Open, too.

Find all the details in the installation guide, linked below.

DataCamp Community: How to install R on Windows, Mac OS X and Ubuntu

Comments

[ssayols]

Just to credit the right people, when you say:

"Multi-threaded math libraries (BLAS). On Windows, Mauricio recommends Microsoft R Open"

I'd add that Microsoft R Open bundles the Intel Math Kernel Library (MKL), which is made by Intel and not Microsoft.

source

https://mran.microsoft.com/documents/rro/multithread

and

https://social.technet.microsoft.com/Forums/azure/en-US/93f35a36-18cf-44f1-8fdd-10f1cfd90e03/what-are-the-optional-math-libraries-in-microsoft-r-open-that-are-multithreaded?forum=ropen