文章基本信息

标题：The Performance of Double Bootstrap Method for Large Sampling Sequence
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作者：Muhamad Safiih Lola ; Nurul Hila Zainuddin
期刊名称：Open Journal of Statistics
印刷版ISSN：2161-718X
电子版ISSN：2161-7198
出版年度：2016
卷号：06
期号：05
页码：805-813
DOI：10.4236/ojs.2016.65066
语种：English
出版社：Scientific Research Publishing
摘要：Studies on the iteration procedure in double bootstrap method have given a great impact on confidence interval performance. However, the procedure was claimed to be complicated and demand intensive computer processor. Considering this problem, an alternative procedure was proposed in this research. Despite of using small sampling sequence, this research was aimed to increase the accuracy estimation using a second replication number which resulted in a large sampling sequence of double bootstrap. In this paper, the alternative double bootstrap method was hybrid onto an example model and its performance was based on Studentised interval. The performance was examined in simulation study and real sample data of sukuk Ijarah. The result showed that hybrid double bootstrap model gave more accurate estimation in terms of its shorter length when dealing with various parameter values and has shown to improve the single bootstrap estimation.
关键词：Double Bootstrap;Confidence Interval;Sampling Sequence;EWMA;Sukuk Ijarah