Kumar S. Using R for Actuarial Science

The prestigious 1998 Association for Computing Machinery Award for software systems was awarded to John Chambers of Bell Labs for the S system. The citation reads, For the S system, which has forever altered how people analyze, visualize, and manipulate data. R is an open source implementation of S and S-PLUS its commercial implementation.
R is an extensible, well documented language and environment with a core group of developers spread out over many countries. The size of its global user group and the diversity in its applications are some of its many strengths. Aimed at actuaries and especially actuarial science students who are pondering over the choice of a computing platform to complement MS Excel, the insurance industry defacto standard, this article makes a case for R.
Designed for statistical computing and embraced by scores of statisticians, most if not all statistical needs of an actuary should be ably served. Hence discussion of its statistical prowess will be conspicuously absent. The next section will highlight some features of potential interest to actuaries. Life contingent computations use mortality tables and most of the important tables are found in the SOA tables database.The third section discusses an implementation of access to this binary database with the intention of providing the readers with a good starting point for computing on the life side. Vectorization, the subject of the penultimate section, is an important concept for computing on R, like on APL and other interpreted vector languages . There we discuss a vectorized solution for an important class of actuarial algorithms.