quantilesonstreamanapplicationtomontecarlosimulation
文献类型：期刊论文
| 作者 | Wang Wei2; Ching Wai Ki1; Wang Shouyang2 ; Yu Lean3
|
| 刊名 | journalofsystemsscienceandinformation
 |
| 出版日期 | 2016 |
| 卷号 | 4期号:4页码:334 |
| ISSN号 | 1478-9906 |
| 英文摘要 | Monte Carlo simulation is an efficient method to estimate quantile. However, it becomes a serious problem when a huge sample size is required but the memory is insufficient. In this paper, we apply the stream quantile algorithm to Monte Carlo simulation in order to estimate quantile with limited memory. A rigorous theoretical analysis on the properties of the ?_n-approximate quantile is proposed in this paper. We prove that if ?_n = o(n~(-1/2)),then the ?_n-approximate α-quantile computed by any deterministic stream quantile algorithm is a consistent and asymptotically normal estimator of the true quantile q_α. We suggest setting ?_n = 1/(n~(1/2) log_(10) n) in practice. Two deterministic stream quantile algorithms, including of GK algorithm and ZW algorithm, are employed to illustrate the performance of the ?_n-approximate quantile. The numerical example shows that the deterministic stream quantile algorithm can provide desired estimator of the true quantile with less memory. |
| 语种 | 英语 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/44505]  |
| 专题 | 系统科学研究所 |
| 作者单位 | 1.香港大学 2.中国科学院数学与系统科学研究院 3.北京化工大学 |
| 推荐引用方式 GB/T 7714 | Wang Wei,Ching Wai Ki,Wang Shouyang,et al. quantilesonstreamanapplicationtomontecarlosimulation[J]. journalofsystemsscienceandinformation,2016,4(4):334. |
| APA | Wang Wei,Ching Wai Ki,Wang Shouyang,&Yu Lean.(2016).quantilesonstreamanapplicationtomontecarlosimulation.journalofsystemsscienceandinformation,4(4),334. |
| MLA | Wang Wei,et al."quantilesonstreamanapplicationtomontecarlosimulation".journalofsystemsscienceandinformation 4.4(2016):334. |
入库方式： OAI收割
来源：数学与系统科学研究院
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