Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

May 5, 2016

Efficient R programming

Filed under: Programming,R — Patrick Durusau @ 9:24 am

Efficient R programming by Colin Gillespie and Robin Lovelace.

From the present text of Chapter 2:

An efficient computer set-up is analogous to a well-tuned vehicle: its components work in harmony, it is well-serviced, and it is fast. This chapter describes the software decisions that will enable a productive workflow. Starting with the basics and moving to progressively more advanced topics, we explore how the operating system, R version, startup files and IDE can make your R work faster (though IDE could be seen as basic need for efficient programming). Ensuring correct configuration of these elements will have knock-on benefits in many aspects of your R workflow. That’s why we cover them at this early stage (hardware, the other fundamental consideration, is covered in the next chapter). By the end of this chapter you should understand how to set-up your computer and R installation (skip to section 2.3 if R is not already installed on your computer) for optimal computational and programmer efficiency. It covers the following topics:

  • R and the operating systems: system monitoring on Linux, Mac and Windows
  • R version: how to keep your base R installation and packages up-to-date
  • R start-up: how and why to adjust your .Rprofile and .Renviron files
  • RStudio: an integrated development environment (IDE) to boost your programming productivity
  • BLAS and alternative R interpreters: looks at ways to make R faster

For lazy readers, and to provide a taster of what’s to come, we begin with our ‘top 5’ tips for an efficient R set-up. It is important to understand that efficient programming is not simply the result of following a recipe of tips: understanding is vital for knowing when to use a memorised solution to a problem and when to go back to first principles. Thinking about and understanding R in depth, e.g. by reading this chapter carefully, will make efficiency second nature in your R workflow.

Nope, go see Chapter 2 if you want the top 5 tips for efficient R set-up.

The text and code are being developed at the website and the authors welcome “pull requests and general comments.”

Don’t be shy!

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