Sieve bootstrap for time series
Bühlmann, Peter
Bernoulli, Tome 3 (1997) no. 3, p. 123-148 / Harvested from Project Euclid
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We study a bootstrap method which is based on the method of sieves. A linear process is approximated by a sequence of autoregressive processes of order p=p(n), where p(n)→∞, p(n)=o(n) as the sample size n→∞. For given data, we then estimate such an AR(p(n)) model and generate a bootstrap sample by resampling from the residuals. This sieve bootstrap enjoys a nice nonparametric property, being model-free within a class of linear processes.
Publié le : 1997-06-14
Classification:  Akaike information criterion,  AR(∞),  ARMA,  autoregressive approximation,  autoregressive spectrum,  blockwise bootstrap,  linear process,  resampling,  stationary sequence,  threshold model 
@article{1177526726,
     author = {B\"uhlmann, Peter},
     title = {Sieve bootstrap for time series},
     journal = {Bernoulli},
     volume = {3},
     number = {3},
     year = {1997},
     pages = { 123-148},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1177526726}
}

Bühlmann, Peter. Sieve bootstrap for time series. Bernoulli, Tome 3 (1997) no. 3, pp.  123-148. http://gdmltest.u-ga.fr/item/1177526726/