If you have any problems related to the accessibility of any content (or if you want to request that a specific publication be accessible), please contact (firstname.lastname@example.org). We will work to respond to each request in as timely a manner as possible.
Random Variate Generation from Generalized Inverse Gaussian Distribution
AuthorPothula, Prashanth Reddy
AdvisorKozubowski, Tomasz J.
Mathematics and Statistics
AltmetricsView Usage Statistics
We consider the problem of random variate generation from generalized inverse Gaussian (GIG) distribution. The CDF of this distribution does not admit an explicit form, so the standard approach to simulation based its inverse is not the right tool for this problem. Instead, we follow the rejection simulation method, based on the probability density function, which is given explicitly for this distribution. We study the efficiency of this method, and identify an optimal numerical procedure within this framework.