id: 05526941
dt: j
an: 2009b.00476
au: Pino-Mejías, R.; Jiménez-Gamero, M.D.; Enguix-González, A
ti: A Monte Carlo comparison of three consistent bootstrap procedures.
so: InterStat, No. 11, 1-11 (2006).
py: 2006
pu: ,
la: EN
cc: K70 K90
ut: bootstrap; Poisson bootstrap; reduced bootstrap; distribution estimation;
finite sample performance
ci:
li:
ab: Summary: Since bootstrap samples are simple random samples with replacement
from the original sample, the information content of some bootstrap
samples can be very low. To avoid this fact, some authors have proposed
several variants of the classical bootstrap. In this paper we consider
two of them: the sequential or Poisson bootstrap and the reduced
bootstrap. Both of them, like ordinary bootstrap, can yield second
order accurate distribution estimators, that is, the three bootstrap
procedures are asymptotically equivalent. The question that naturally
arises is which of them should be used in a practical situation, in
other words, which of them should be used for finite sample sizes. To
try to answer this question, we have carried out a simulation study.
Although no method was found to exhibit best performance in all the
considered situations, some recommendations are given.
rv: