/nodag

structure recovery without imposing acyclicity

Primary LanguageFortranBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

nodag

structure learning without imposing acyclicity

This repository contains fortran implementation of a proximal gradient method to estimate the structure of a Bayesian network without imposing the acyclicity constraint.

The subrutine NODAG solve the following l1-penalized minus log-likelihood minimization:

argmin  -2log(det(A)) + trace( Sigma AA^t) + lambda ||A||_1

use

The fortran subrutine NODAG can be easily used both from python and R

  • python: compile nodag.f with f2py using f2py -llapack -c -m nodag nodag.f
  • R: compile nodag.f with R CMD SHLIB nodag.f -llapack -lblas

Check the provided examples to see how to load and call the subroutine.