It is well known that R is one of the most used statistical package by the data scientists (researchers, technicians, etc..). This package allows flexibility to adapt already developed functions to their own interests. However, the problem comes when one needs to perform a complex algorithm that requires strong programming level or even to show to worldwide scientists how a new statistical technique works. When this scenario is present, it means that it is time to create your own package in R.
The most In this post we will learn how to make a simple R package only following several steps which are explained in the next paragraphs:
1. Update R version and other relevant tools.
First of all, if you are planning to develop a R package, it is highly recommended to update your R version to newest one. One must take into account that R versions are continuously updating so that your package would be likely to not to work properly. Furthermore, the package called Rtools is necessary to install in your system. This package has several add-ins (such as MinGW compiler) which are helpful for the development of the package.
2. Get to know your Operative System
For Windows System, you have to add to the PATH system variable the whole path where R is installed. For instance, if R is installed in c:, the PATH can be fixed as:
PATH=%PATH%;c:\Rtools\bin;c:\Rtools\perl\bin;c:\Rtools\MinGW\bin;
c:\texmf\miktex\bin;c:\R-2.15.0\bin;
3. Decide the name and the kind of the package wanted to build.
This step is the most important. First of all, the package name can only be composed by numbers and letters and it is highly recommended to start it with a letter.
When building the functions belonging to the package, it is very important the arrangement of the files where the functions are written. There are two possible situations: (1) all functions in a file; (2) each function in its own file. Both options are extreme since (1) writing all functions in a file could overload the system and (2) writing many functions in its own files implies having multiple files that should be packed. So, in order to search an alternative to these options, I suggest grouping related functions into the same files.
4. Edit some files
Once the previous steps are done, several files should be filled out/edited so that any R user who wants to use the functions within the package is able to understand what the function does.
First of all, it is obligatory to fill in a file named DESCRIPTION. It is used to describe the package, with author, and license conditions in a structured text format that is readable by computers and by people.
Secondly, a tutorial of the package (called as VIGNETTES) should be written. An extended description with reproducible examples shows the performance of each function within the repository.
5. Building, installing and executing the package
As final step, you have to mix all the components in a file by means of different software commands. Using the package.skeleton() function (see below) one can create the desired mypkg package:
package.skeleton(list=c(“f”,”g”,”h”,”i”),name=”mypkg”)
where f, g, h, i¸ are all the functions belonging to the repository.
Once mypkg is created, the next step is to install it in our R system. You can use the common ways to perform it but I would advise using R commands to do that (R CMD INSTALL). Load the package and execute it. It is time to enjoy it!!
This has been a summary of the steps to follow for a R package repository development. Now it is your challenge!!!
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