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Subsampling confidence intervals for parameters of atmospheric time series: Block size choice and calibration
(2005)
Problems of practical implementation of the computer intensive subsampling methodology are addressed by Monte Carlo simulations of a situation typical for atmospheric time series. The motivating data were collected under ...
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, ...
Subsampling inference for the mean of heavy-tailed long-memory time series
(2012)
In this article, we revisit a time series model introduced by MCElroy and Politis (2007a) and generalize it in several ways to encompass a wider class of stationary, nonlinear, heavy-tailed time series with long memory. ...
Block bootstrap theory for multivariate integrated and cointegrated processes
(2014)
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 ...
LASSO order selection for sparse autoregression: a bootstrap approach
(2017)
Autoregressive models are widely employed for predictions and other inferences in many scientific fields. While the determination of their order is in general a difficult and critical step, this task becomes more complicated ...