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