No CrossRef data available.
Article contents
Deep-Penetration Calculations for Scattering Neutrons by Importance Sampling
Published online by Cambridge University Press: 27 July 2009
Abstract
Neutron scatter in a homogeneous solid is modelled as a one-dimensional i.i.d. random walk with killing. Importance sampling is used to estimate the extremely small probability that the random walk crosses a large level before killing occurs. The theory of large deviations provides insight into the selection of the probability measure used in the simulations. A sample problem demonstrates the variance reduction possible when this technique is used.
- Type
- Research Article
- Information
- Probability in the Engineering and Informational Sciences , Volume 8 , Issue 2 , April 1994 , pp. 201 - 211
- Copyright
- Copyright © Cambridge University Press 1994
References
1.Bucklew, J.A. (1990). Large deviation techniques in decision, simulation, and estimation. New York: Wiley Interscience.Google Scholar
2.Cramer, S.N., Gonnord, J., & Hendricks, J.S. (1986). Monte Carlo techniques for analyzing deep-penetration problems. Nuclear Science and Engineering 92: 280–288.CrossRefGoogle Scholar
3.Glynn, P.W. & Iglehart, D.L. (1989). Importance sampling for stochastic simulations. Management Science 35: 1367–1392.CrossRefGoogle Scholar
4.Lehtonen, T. & Nyrhinen, H. (1992). Simulating level-crossing probabilities by importance sampling. Advances in Applied Probability 24: 858–874.CrossRefGoogle Scholar
5.Murthy, K.P.N. & Indira, R. (1986). Analytical results of variance reduction characteristics of biased Monte Carlo for deep-penetration problems. Nuclear Science and Engineering 92: 482–487.CrossRefGoogle Scholar
7.Rockafellar, R.T. (1970). Convex analysis. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
8.Siegmund, D. (1976). Importance sampling in the Monte Carlo study of sequential tests. Annals of Statistics 4: 673–684.CrossRefGoogle Scholar