Abstract
A method for Monte Carlo importance sampling with parametric dependence is proposed. The method depends on scaling of the particle tracks for a certain number of generated histories, to determine the position of the optimal biasing parameters. Computational results for a model problem show that difficulties pointed out by previous authors as to the occurrence of infinite variances or under-sampling can be easily understood and spotted by the careful user, and eliminated so as to obtain dependable results with moderate numbers of particle histories.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 198-206 |
| Number of pages | 9 |
| Journal | Atomkernenergie, Kerntechnik |
| Volume | 39 |
| Issue number | 3 |
| State | Published - 1981 |
| Externally published | Yes |
ASJC Scopus subject areas
- General Engineering