Browsing by Subject "Block bootstrap"
Now showing items 1-9 of 9
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Article
Automatic Block-Length Selection for the Dependent Bootstrap
(2004)We review the different block bootstrap methods for time series, and present them in a unified framework. We then revisit a recent result of Lahiri [Lahiri, S. N. (1999b). Theoretical comparisons of block bootstrap methods, ...
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Article
Banded and tapered estimates for autocovariance matrices and the linear process bootstrap
(2010)We address the problem of estimating the autocovariance matrix of a stationary process. Under short range dependence assumptions, convergence rates are established for a gradually tapered version of the sample autocovariance ...
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Article
Block Bootstrap Theory for Multivariate Integrated and Cointegrated Processes
(2015)We develop some asymptotic theory for applications of block bootstrap resampling schemes to multivariate integrated and cointegrated time series. It is proved that a multivariate, continuous-path block bootstrap scheme ...
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Article
Correction to automatic block-length selection for the dependent bootstrap by D. Politis and H. White
(2009)A correction on the optimal block size algorithms of Politis and White (2004) is given following a correction of Lahiri's (Lahiri 1999) theoretical results by Nordman (2008).
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Fixed b subsampling and the block bootstrap: Improved confidence sets based on p-value calibration
(2013)Subsampling and block-based bootstrap methods have been used in a wide range of inference problems for time series. To accommodate the dependence, these resampling methods involve a bandwidth parameter, such as the subsampling ...
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Article
The Impact of Bootstrap Methods on Time Series Analysis
(2003)Sparked by Efron's seminal paper, the decade of the 1980s was a period of active research on bootstrap methods for independent data - mainly i.i.d. or regression set-ups. By contrast, in the 1990s much research was directed ...
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Article
K-sample subsampling in general spaces: The case of independent time series
(2010)The problem of subsampling in two-sample and K-sample settings is addressed where both the data and the statistics of interest take values in general spaces. We focus on the case where each sample is a stationary time ...
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Some properties of the autoregressive-aided block bootstrap
(2017)We investigate properties of a hybrid bootstrap procedure for general, strictly stationary sequences, called the autoregressive-aided block bootstrap which combines a parametric autoregressive bootstrap with a nonparametric ...
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Article
Valid resampling of higher-order statistics using the linear process bootstrap and autoregressive sieve bootstrap
(2013)We show that the linear process bootstrap (LPB) and the autoregressive sieve bootstrap (AR sieve) are, in general, not valid for statistics whose large-sample distribution depends on moments of order higher than two, ...