README.md

In raredd/trainr: Analysis project and presentation.

Better practices for statistical computing in r

20 May 2015

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Download a zip file of this repo or clone to your computer:

mkdir trainr
cd trainr
git clone https://github.com/raredd/trainr.git

This repo includes an r package. For information on building r packages, see Hadley's intro.

To get started, you should download and install rstudio and also a few r packages.

install.packages(c("devtools", "roxygen2", "testthat", "knitr"))

(I have just learned that rstudio also takes care of the compiler and command line tools you will need to build r packages, but if you are not using rstudio, you will need to install either Rtools for windows machines, xcode + command line tools for macintosh (you will also need to sign up for a [free] apple id), or install the development tools package, r-base-dev, for linux distros.)

After installing rstudio and the four packages, run the following in r to see if you are ready to build packages (this function should return TRUE):

devtools::has_devel()

Finally, open trainr.Rproj to get started.

raredd/trainr documentation built on May 27, 2019, 2:03 a.m.