Add to ORKGPolitis and White (2004) reviewed the problem of (nonparametric) bootstrapping for time series, and presented different block bootstrap methods in a unified way. In addition, results of Lahiri (1999) were reviewed, a corrected bound was suggested on the asymptotic relative efficiency (ARE) of different methods, and practically useful estimators of the optimal bloc
grantor: University of TorontoThe bootstrap was introduced in 1979 as a computer-intensive...
This paper considers the block selection problem for a block bootstrap vari-ance estimator applied t...
SUMMARY The block bootstrap for time series consists in randomly resampling blocks of consecutive v...
We address the issue of optimal block choice in applications of the block bootstrap to dependent dat...
The block bootstrap confidence interval for dependent data can outperform the conventional normal ap...
In this study, we propose sufficient time series bootstrap methods that achieve better results than ...
This paper weakens the size and moment conditions needed for typical block bootstrap methods (i.e. t...
This paper establishes that the minimum error rates in coverage probabilities of one- and sym-metric...
This paper discusses the problem of choosing the optimal block length for two block bootstrap method...
The purpose of this paper is to introduce and examine two alternative, although similar, approaches ...
This Diploma thesis deals with principles, asymptotic properties and comparison of bootstrap methods...
The paper contains a description of four different block bootstrap methods, i.e., non-overlapping bl...
We show that a bootstrap model selection criterion constructed by directly plugging-in a consistent ...
This paper considers the problem of choosing the number of bootstrap repetitions B for bootstrap sta...
Consistency and optimality of block bootstrap schemes for distribution and variance estimation of sm...
grantor: University of TorontoThe bootstrap was introduced in 1979 as a computer-intensive...
This paper considers the block selection problem for a block bootstrap vari-ance estimator applied t...
SUMMARY The block bootstrap for time series consists in randomly resampling blocks of consecutive v...
We address the issue of optimal block choice in applications of the block bootstrap to dependent dat...
The block bootstrap confidence interval for dependent data can outperform the conventional normal ap...
In this study, we propose sufficient time series bootstrap methods that achieve better results than ...
This paper weakens the size and moment conditions needed for typical block bootstrap methods (i.e. t...
This paper establishes that the minimum error rates in coverage probabilities of one- and sym-metric...
This paper discusses the problem of choosing the optimal block length for two block bootstrap method...
The purpose of this paper is to introduce and examine two alternative, although similar, approaches ...
This Diploma thesis deals with principles, asymptotic properties and comparison of bootstrap methods...
The paper contains a description of four different block bootstrap methods, i.e., non-overlapping bl...
We show that a bootstrap model selection criterion constructed by directly plugging-in a consistent ...
This paper considers the problem of choosing the number of bootstrap repetitions B for bootstrap sta...
Consistency and optimality of block bootstrap schemes for distribution and variance estimation of sm...
grantor: University of TorontoThe bootstrap was introduced in 1979 as a computer-intensive...
This paper considers the block selection problem for a block bootstrap vari-ance estimator applied t...
SUMMARY The block bootstrap for time series consists in randomly resampling blocks of consecutive v...