Name
Abstract | ||
|---|---|---|
We consider the setting of estimating the mean of a random variable by a sequential stopping rule Monte Carlo (MC) method. The performance of a typical second moment based sequential stopping rule MC method is shown to be unreliable in such settings both by numerical examples and through analysis. By analysis and approximations, we construct a higher moment based stopping rule which is shown in numerical examples to perform more reliably and only slightly less efficiently than the second moment based stopping rule. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1137/130911433 | SIAM JOURNAL ON SCIENTIFIC COMPUTING |
Keywords | Field | DocType |
Monte Carlo methods,optimal stopping,sequential stopping rules,nonasymptotic | Mathematical optimization,Random variable,Monte Carlo method,Optimal stopping,Computational mathematics,Sequential estimation,Stopping rule,Mathematics,Second moment of area | Journal |
Volume | Issue | ISSN |
36 | 2 | 1064-8275 |
Citations | PageRank | References |
3 | 0.62 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Bayer | 1 | 5 | 1.37 |
| Håkon Hoel | 2 | 21 | 4.02 |
| Erik von Schwerin | 3 | 38 | 3.13 |
| Raul | 4 | 477 | 54.12 |