English

Holonomic gradient method for the probability content of a simplex region with a multivariate normal distribution

Statistics Theory 2020-03-04 v2 Computation Statistics Theory

Abstract

We use the holonomic gradient method to evaluate the probability content of a simplex region under a multivariate normal distribution. This probability equals to the integral of the probability density function of the multivariate Gaussian distribution on the simplex region. For this purpose, we generalize the inclusion--exclusion identity which was given for polyhedra, to the faces of a polyhedron. This extended inclusion--exclusion identity enables us to calculate the derivatives of the function associated with the probability content of a polyhedron in general position. We show that these derivatives can be written as integrals of the faces of the polyhedron.

Keywords

Cite

@article{arxiv.1512.06564,
  title  = {Holonomic gradient method for the probability content of a simplex region with a multivariate normal distribution},
  author = {Tamio Koyama},
  journal= {arXiv preprint arXiv:1512.06564},
  year   = {2020}
}

Comments

22 pages, 2 figures

R2 v1 2026-06-22T12:14:48.564Z