Random variate generation for exponential and gamma tilted stable distributions

Qu, Yan, Dassios, Angelos ORCID: 0000-0002-3968-2366 and Zhao, Hongbiao (2021) Random variate generation for exponential and gamma tilted stable distributions. ACM Transactions on Modeling and Computer Simulation, 31 (4). ISSN 1049-3301

Text (Random Variate Generation for Exponential and Gamma Tilted Stable Distributions) - Accepted Version Download (1MB)

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Abstract

We develop a new efficient simulation scheme for sampling two families of tilted stable distributions: exponential tilted stable (ETS) and gamma tilted stable (GTS) distributions. Our scheme is based on two-dimensional single rejection. For the ETS family, its complexity is uniformly bounded over all ranges of parameters. This new algorithm outperforms all existing schemes. In particular, it is more efficient than the well-known double rejection scheme, which is the only algorithm with uniformly bounded complexity that we can find in the current literature. Beside the ETS family, our scheme is also flexible to be further extended for generating the GTS family, which cannot easily be done by extending the double rejection scheme. Our algorithms are straightforward to implement, and numerical experiments and tests are conducted to demonstrate the accuracy and efficiency.

Item Type:	Article
Official URL:	https://dl.acm.org/journal/tomacs
Additional Information:	© 2021 Association for Computing Machinery
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date Deposited:	08 Feb 2021 10:54
Last Modified:	02 Nov 2024 01:51
URI:	http://eprints.lse.ac.uk/id/eprint/108593

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