| Autor: |
Bounnite, Mohamed Yasser, Nasroallah, Abdelaziz |
| Předmět: |
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| Zdroj: |
Monte Carlo Methods & Applications; Dec2015, Vol. 21 Issue 4, p301-312, 12p, 4 Charts, 7 Graphs |
| Abstrakt: |
The standard Coupling From The Past (CFTP) algorithm is an interesting tool to sample from exact stationary distribution of a Markov chain. But it is very expensive in time consuming for large chains. There is a monotone version of CFTP, called MCFTP, that is less time consuming for monotone chains. In this work, we propose two techniques to get monotone chain allowing use of MCFTP: widening technique based on adding two fictitious states and clustering technique based on partitioning the state space in clusters. Usefulness and efficiency of our approaches are showed through a sample of Markov Chain Monte Carlo simulations. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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