Introduction to C

All statisticians should be proficient in C (for speed), perl (for data manipulation), and R (for interactive analyses and graphics). Think "CPR".

I use C for all computationally intensive tasks, but I no longer write stand-alone C programs. All of my C code is written within add-on packages for R. This makes the data input/output easy, and we don't need to worry about the interface. Plus, the results come out within R, and so they are immediately available for further analyses. Also, the R package incorporates documentation. Most importantly, R has an extensive library of mathematical and statistical functions that we can use directly from our C code.

While I intended this page to provide an introduction similar to my Introduction to Perl page, instead, I am leaving this as a list of links. The Writing R Extensions manual is particularly important, as it discusses package creation, the interface to C, and how to get at the R's library of code.



R manuals

Math/stat subroutine libraries

All I need is available with R.

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Last modified: Mon Feb 4 08:46:58 2013