Lisp-Stat is conceptually similar to R and will be familiar to most people from that ecosystem. It is suitable for both exploratory data analysis as well as front-line production deployments. Common Lisp is currently used at Google in several high-availability, high-volume transactional systems.
We had a few requirements when evaluating options. Specifically the system had to:
- Work well in the kind of exploratory environment conducive to analytics and AI
- Be robust enough to work in an enterprise production environment
- Be available under a license without source code restrictions
Common Lisp was the only framework that met all these requirements.
Probably the most important reasons though are given in the paper by Ross Ihaka, one of the originators of the R language, Lisp as a Base for a Statistical Computing System about the deficiencies in R and the inability to compile to machine code (among other issues). The same is true of Python. In that paper he argues for Lisp as a replacement for R.
What does Lisp-Stat do?
Lisp-Stat provides support for vectorized mathematical operations and a comprehensive set of statistical methods that are implemented using the latest numerical algorithms. In addition, Common Lisp provides a dynamic programming environment (REPL), an excellent object-oriented facility (CLOS) and meta-object protocol (MOP).
Lisp-Stat is functional today and in daily use on several projects. It has an archive of libraries from XLISP-STAT that can be used with the aid of a compatibility package (XLS-compat). The archive includes packages for linear models, KNN, advanced statistics, temporal/spatial reasoning and a Lisp version of the NSWC Library of Mathematics Subroutines. It also includes the Cephes mathmatical library for accurate statistical distribution calculations.
For more on what Lisp-Stat can do, see getting started and the overview.
What’s next for Lisp-Stat?
Lisp-Stat is an open source project and we welcome patches and contributions. Both code and documentation contributions help, and documenting the code, writing tutorials, etc., is an excellent way to learn the ins and outs of a statistical system. We hope to continue to make improvements to the system along with the Lisp-Stat community.
Visit the github repository to see what we’re currently working on. If there is something you would like to see in Lisp-Stat, please create an issue yourself - or assign yourself an issue if you would like to fix or add something. See our contribution guidelines for more information.