Name
Title | ||
|---|---|---|
Improving p-value approximation and level accuracy of Monte Carlo tests by quasi-Monte Carlo methods |
Abstract | ||
|---|---|---|
We argue and show empirically that for the Monte Carlo test, if the pseudo-random numbers are replaced by a randomized low discrepancy sequence, the actual errors in approximating the p-value are smaller and the deviations of the exact level from the nominal level have higher potential to be smaller. Hence in real applications the proposed method, called randomized quasi-Monte Carlo test, is suggested to be used instead of the traditional Monte Carlo test. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1080/03610918.2019.1667389 | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION |
Keywords | DocType | Volume |
Monte Carlo test, Quasi-Monte Carlo, Resampling, Sobol' sequence | Journal | 51 |
Issue | ISSN | Citations |
3 | 0361-0918 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sung Nok Chiu | 1 | 12 | 3.37 |
| Kwong Ip Liu | 2 | 9 | 2.15 |