Large deviations in rare events simulation: examples, counterexamples and alternatives
(2002) Proceedings of Fourth International Conference on Monte Carlo and QuasiMonte Carlo Methods in Scientific Computing In MonteCarlo and QuasiMonte Carlo Methods 2000. Proceedings of a Conference p.19 Abstract
 When simulating small probabilities, say of order 10<sup>6</sup> or less, by importance sampling, an established principle is to choose the importance sampling distribution as close to the conditional distribution given the rare event as possible. Implementing this often leads into large deviations calculations and exponential change of measure. We survey some of the standard examples where this approach works and supplement existing counterexamples with new ones. Difficulties often arise as consequence of reflecting barriers and we present an algorithm which at least in simple cases is able to deal with this problem. Also the case of heavytailed distributions is considered
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/record/611224
 author
 Asmussen, Sören
 organization
 publishing date
 2002
 type
 Chapter in Book/Report/Conference proceeding
 publication status
 published
 subject
 keywords
 conditional distribution, heavytailed distributions, importance sampling, rare event, small probabilities, rare events simulation
 in
 MonteCarlo and QuasiMonte Carlo Methods 2000. Proceedings of a Conference
 pages
 1  9
 publisher
 Springer
 conference name
 Proceedings of Fourth International Conference on Monte Carlo and QuasiMonte Carlo Methods in Scientific Computing
 external identifiers

 WOS:000175526000001
 ISBN
 354042718X
 language
 English
 LU publication?
 yes
 id
 5ac571971d73417a9ea22fe7392cf67e (old id 611224)
 date added to LUP
 20071123 14:55:11
 date last changed
 20160416 08:21:59
@misc{5ac571971d73417a9ea22fe7392cf67e, abstract = {When simulating small probabilities, say of order 10<sup>6</sup> or less, by importance sampling, an established principle is to choose the importance sampling distribution as close to the conditional distribution given the rare event as possible. Implementing this often leads into large deviations calculations and exponential change of measure. We survey some of the standard examples where this approach works and supplement existing counterexamples with new ones. Difficulties often arise as consequence of reflecting barriers and we present an algorithm which at least in simple cases is able to deal with this problem. Also the case of heavytailed distributions is considered}, author = {Asmussen, Sören}, isbn = {354042718X}, keyword = {conditional distribution,heavytailed distributions,importance sampling,rare event,small probabilities,rare events simulation}, language = {eng}, pages = {19}, publisher = {ARRAY(0x833f9b8)}, series = {MonteCarlo and QuasiMonte Carlo Methods 2000. Proceedings of a Conference}, title = {Large deviations in rare events simulation: examples, counterexamples and alternatives}, year = {2002}, }