In this study, we propose sufficient time series bootstrap methods that achieve better results than conventional non-overlapping block bootstrap, but with less computing time and lower standard errors of estimation. Also, we propose using a new technique using ordered bootstrapped blocks, to better preserve the dependency structure of the original data. The performance of the proposed methods are compared in a simulation study for MA(2) and AR(2) processes and in an example. The results show that our methods are good competitors that often exhibit improved performance over the conventional block methods
Abstract. We develop some asymptotic theory for applications of block bootstrap resampling schemes t...
In this paper, we introduce an idea we refer to as sufficient bootstrapping, which is based on retai...
This paper discusses the problem of choosing the optimal block length for two block bootstrap method...
In this study, we propose sufficient time series bootstrap methods that achieve better results than ...
The paper contains a description of four different block bootstrap methods, i.e., non-overlapping bl...
This Diploma thesis deals with principles, asymptotic properties and comparison of bootstrap methods...
Abstract. The application of a parametric time series model to a water resources problem involves se...
The purpose of this paper is to introduce and examine two alternative, although similar, approaches ...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
Politis and White (2004) reviewed the problem of (nonparametric) bootstrapping for time series, and ...
In this paper, we adapt sufficient and ordered non-overlapping block bootsrap methods into jackknife...
We develop some asymptotic theory for applications of block bootstrap resampling schemes to multiva...
It is common in parametric bootstrap to select the model from the data, and then treat as if it were...
SUMMARY The block bootstrap for time series consists in randomly resampling blocks of consecutive v...
Abstract. We develop some asymptotic theory for applications of block bootstrap resampling schemes t...
In this paper, we introduce an idea we refer to as sufficient bootstrapping, which is based on retai...
This paper discusses the problem of choosing the optimal block length for two block bootstrap method...
In this study, we propose sufficient time series bootstrap methods that achieve better results than ...
The paper contains a description of four different block bootstrap methods, i.e., non-overlapping bl...
This Diploma thesis deals with principles, asymptotic properties and comparison of bootstrap methods...
Abstract. The application of a parametric time series model to a water resources problem involves se...
The purpose of this paper is to introduce and examine two alternative, although similar, approaches ...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
Politis and White (2004) reviewed the problem of (nonparametric) bootstrapping for time series, and ...
In this paper, we adapt sufficient and ordered non-overlapping block bootsrap methods into jackknife...
We develop some asymptotic theory for applications of block bootstrap resampling schemes to multiva...
It is common in parametric bootstrap to select the model from the data, and then treat as if it were...
SUMMARY The block bootstrap for time series consists in randomly resampling blocks of consecutive v...
Abstract. We develop some asymptotic theory for applications of block bootstrap resampling schemes t...
In this paper, we introduce an idea we refer to as sufficient bootstrapping, which is based on retai...
This paper discusses the problem of choosing the optimal block length for two block bootstrap method...