Fortran Wiki
FSML

Summary

FSML is a toolkit for statistical and machine learning (ML) procedures, including basic statistics (e.g., correlation), hypothesis tests (e.g., Mann–Whitney U, ANOVA), linear parametric methods and models (e.g., multiple OLS regression, discriminant analysis), and non-linear statistical and ML procedures (e.g., k-means clustering).

To make it more accessible to contributors, students, researchers, and other users, it is kept relatively simple (KISS), overengineering is avoided, requirements are minimal (stdlib for linear algebra, and fpm for building/distributing), and much of the API should look familiar to those used to popular packages for other languages (Python and R).

Code and Documentation

The code can be found here, and its documentation (with Handbook and API doc pages) can be found on fsml.mutz.science. It’s MIT licenced, so it’s compatible with Fortran-lang projects, and the API documentation follows a similar style as Fortran-lang stdlib.

Paper

The associated paper Mutz S.G., 2025 was published in JOSS (Journal of Open Source Software). A “thank you” goes out to the editor (J. Atkinson) and reviewers (I. Pribec and M. A. Kowalski) for their time and effort.

Blog Post

This blog post provides a little more context, notes on some design choices, and where it fits into the Fortran statistics and ML ecosystem.