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Random Variate Generation from Generalized Inverse Gaussian Distribution
Date
2011Type
ThesisDepartment
Mathematics and Statistics
Degree Level
Master's Degree
Abstract
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.
Permanent link
http://hdl.handle.net/11714/4019Subject
GaussianGeneralized
Inverse
Random Variate
Variate
Additional Information
Committee Member | Zaliapian, Ilya; Lu, Minggen |
---|---|
Rights | In Copyright(All Rights Reserved) |
Rights Holder | Author(s) |