TITLE:
The Performance of Double Bootstrap Method for Large Sampling Sequence
AUTHORS:
Muhamad Safiih Lola, Nurul Hila Zainuddin
KEYWORDS:
Double Bootstrap, Confidence Interval, Sampling Sequence, EWMA, Sukuk Ijarah
JOURNAL NAME:
Open Journal of Statistics,
Vol.6 No.5,
October
18,
2016
ABSTRACT: 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.