Simulation of truncated normal variables

TL;DR

This paper introduces algorithms for simulating truncated normal variables, including multivariate cases with various covariance structures, facilitating applications requiring restricted normal distributions.

Contribution

The paper presents novel simulation algorithms for one-sided, two-sided, and multivariate truncated normal distributions with arbitrary covariance matrices.

Findings

Algorithms successfully generate truncated normal variables.

Applicable to multivariate cases with complex covariance structures.

Enhances simulation methods for restricted normal distributions.

Abstract

We provide in this paper simulation algorithms for one-sided and two-sided truncated normal distributions. These algorithms are then used to simulate multivariate normal variables with restricted parameter space for any covariance structure.