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Simulation of random variates with the Morgenstern distribution
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Oleg A. Makhotkin
Published/Copyright:
October 1, 2015
Abstract
Five algorithms for the simulation of random vectors with the bivariate Morgenstern distribution are described and realized. The run-time efficiencies of these algorithms are estimated so that the fastest one is determined. It uses the presentation of the Morgenstern distribution density as the sum of the bilinear finite elements.
MSC: 65C05
Received: 2013-12-11
Accepted: 2015-8-26
Published Online: 2015-10-1
Published in Print: 2015-12-1
© 2015 by De Gruyter
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Articles in the same Issue
- Frontmatter
- The parallel replica method for computing equilibrium averages of Markov chains
- Mathematical verification of the Monte Carlo maximum cross-section technique
- Infinite-dimensional Monte-Carlo integration
- Widening and clustering techniques allowing the use of monotone CFTP algorithm
- Constructing positivity preserving numerical schemes for the two-factor CIR model
- Simulation of random variates with the Morgenstern distribution
Keywords for this article
Morgenstern distribution;
simulation algorithms;
computer-aided experiments
Articles in the same Issue
- Frontmatter
- The parallel replica method for computing equilibrium averages of Markov chains
- Mathematical verification of the Monte Carlo maximum cross-section technique
- Infinite-dimensional Monte-Carlo integration
- Widening and clustering techniques allowing the use of monotone CFTP algorithm
- Constructing positivity preserving numerical schemes for the two-factor CIR model
- Simulation of random variates with the Morgenstern distribution
