Category: R Programming

Microsoft Azure ML provides over 500 individual R packages for use in R scripts. It is almost certain, however, that at some point you will wish to use an R package not available by default. Several years ago, before Revolution Analytics was acquired by Microsoft, Andrie deVries created a very useful package called miniCRAN. This […]

Statisticians have developed a remarkably powerful set of tools for analyzing normally distributed data. Too bad real data is never normally distributed. Fortunately for us, most of the time “close enough” is all we really need. But how are we to know? One quick and effective method is a look at a Q-Q plot. The […]

It’s impossible to imagine a data scientist who does not have to randomly sample datasets on a regular basis. Most employ the useful and easy function sample( ), defined in R’s base namespace. Let’s take a closer look at sample( ) and then take a look at a flexible alternative that is just as easy […]

Anyone who has ever done a linear regression in R has seen an R formula. R formulae are examples of the Wilkinson notation, sometimes called the Wilkinson-Rogers notation. This same notation is used by other applications including Matlab and Octave to indicate relationships between variables. In most cases, R users have seen the Wilkinson notation […]

When R starts up, it looks for several files to initialize its configuration. R has its own configuration file called Rprofile.site located in the /etc folder. It is probably wise not to mess with this file unless you are very confident in your understanding. Most R users are aware that during startup, R reads an […]