quantilesonstreamanapplicationtomontecarlosimulation

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	quantilesonstreamanapplicationtomontecarlosimulation
	Wang Wei 1; Ching Wai Ki 2; Wang Shouyang1 ; Yu Lean 3
	2016-01-01
发表期刊	journalofsystemsscienceandinformation
ISSN	1478-9906
卷号	4 期号:4 页码:334
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
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/44506
专题	系统科学研究所
作者单位	1.中国科学院数学与系统科学研究院 2.香港大学 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.