Efficient sampling from truncated bivariate Gaussians via Box-Muller transformation
Efficient sampling from truncated bivariate Gaussians via Box-Muller transformation
Many practical simulation tasks demand procedures to draw samples efficiently from multivariate truncated Gaussian distributions. Introduced is a novel rejection approach, based on the Box-Muller transformation, to generate samples from a truncated bivariate Gaussian density with an arbitrary support. Furthermore, for an important class of support regions the new method …