Efficient Simultaneous Simulation of Markov Chains

Carsten Wächter () and Alexander Keller ()
Additional contact information
Carsten Wächter: Ulm University
Alexander Keller: Ulm University

A chapter in Monte Carlo and Quasi-Monte Carlo Methods 2006, 2008, pp 669-684 from Springer

Abstract: Summary Markov chains can be simulated efficiently by either high-dimensional low discrepancy point sets or by padding low dimensional point sets. Given an order on the state space, both approaches can be improved by sorting the ensemble of Markov chains. We analyze deterministic approaches resulting in algorithmic simplifications and provide intuition when and why the sorting works. Then we discuss the efficiency of different sorting strategies for the example of light transport simulation.

Keywords: Markov Chain; Monte Carlo; Travel Salesman Problem; Light Transport; Test Scene (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-74496-2_41

Ordering information: This item can be ordered from
http://www.springer.com/9783540744962

DOI: 10.1007/978-3-540-74496-2_41

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().