Browsing by Subject "Subsampling"
Now showing items 1-17 of 17
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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
Computer-intensive rate estimation, diverging statistics and scanning
(2007)A general rate estimation method is proposed that is based on studying the in-sample evolution of appropriately chosen diverging/converging statistics. The proposed rate estimators are based on simple least squares arguments, ...
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Article
Distribution theory for the studentized mean for long, short, and negative memory time series
(2013)We consider the problem of estimating the variance of the partial sums of a stationary time series that has either long memory, short memory, negative/intermediate memory, or is the first-difference of such a process. The ...
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Extrapolation of subsampling distribution estimators: The i.i.d. and strong mixing cases
(2001)Politis & Romano (1994) proposed a general subsampling methodology for the construction of large-sample confidence regions for an arbitrary parameter under minimal conditions. Nevertheless, the subsampling distribution ...
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Article
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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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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Inference for autocorrelations in the possible presence of a unit root
(2004)We consider the problem of making inference for the autocorrelations of a time series in the possible presence of a unit root. Even when the underlying series is assumed to be strictly stationary, the robustness against a ...
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Article
Large sample theory for statistics of stable moving averages
(2004)We study the limit behavior of the partial sums, sample variance, and periodogram of the stable moving average process x(t)= ∫ ψ(t + x)double struck M sign (dx) explored in Resnick, S., Samorodnitsky, G., and Xue, F. (1999). ...
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Article
Moment estimation for statistics from marked point processes
(2001)In spatial statistics the data typically consist of measurements of some quantity at irregularly scattered locations
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Moment-based tail index estimation
(2007)A general method of tail index estimation for heavy-tailed time series, based on examining the growth rate of the logged sample second moment of the data was proposed and studied in Meerschaert and Scheffler (1998. A simple ...
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Article
Stable marked point processes
(2007)In many contexts such as queuing theory, spatial statistics, geostatistics and meteorology, data are observed at irregular spatial positions. One model of this situation involves considering the observation points as ...
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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 ...
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Subsampling for heteroskedastic time series
(1997)In this article, a general theory for the construction of confidence intervals or regions in the context of heteroskedastic-dependent data is presented. The basic idea is to approximate the sampling distribution of a ...
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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. ...
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Tapered block bootstrap
(2001)We introduce and study tapered block bootstrap methodology that yields an improvement over the well-known block bootstrap for time series of Künsch (1989). The asymptotic validity and the favourable bias properties of the ...
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Testing Time Series Linearity. Traditional and Bootstrap Methods
(2012)We review the notion of time series linearity and describe recent advances in linearity and Gaussianity testing via data resampling methodologies. Many advances have been made since the first published tests of linearity ...
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Weak convergence of dependent empirical measures with application to subsampling in function spaces
(1999)Consider the problem of inference for a parameter of a stationary time series, where the parameter takes values in a metric space (such as a function space). In this paper, we develop asymptotic theory based on subsampling ...