Improved algorithms for rare event simulation with heavy tails

By Søren Asmussen, Dirk P. Kroese. Advances in Applied Probability, 2006

143 citations recorded by the source corpus.

Subfields: Demography, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/f294dc1c905bd08bbc057fb376bb315718e6f9e2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Demography

1. Peter W. Glynn
2. Jose H. Blanchet
3. Persi Diaconis
4. Sourav Chatterjee

In Management Information Systems

1. Jose H. Blanchet
2. Persi Diaconis
3. Sourav Chatterjee

In Management Science and Operations Research

1. Jingcheng Liu
2. Jose H. Blanchet
3. Peter W. Glynn
4. Persi Diaconis
5. Sourav Chatterjee
6. Daniel Lemire

Citations in the corpus

• State-dependent importance sampling for regularly varying random walks (2008, background): “Keywords: State dependent; importance sampling; regularly varying; random walk; heavy tail; strong efficiency; rare-event simulation 2000 Mathematics Subject Classification: Primary 60G50; 60J05; 68W40 Secondary 60G70”
• Efficient rare-event simulation for the maximum of heavy-tailed random walks (2008, background): “More recently, Asmussen and Kroese (2006) proposed other logarithmically efficient importance sampling algorithms for the M/G/ 1 queue that seem to have excellent performance in practice.”