Two frequency domain bootstrap methods for weakly stationary time series will be proposed. The motivations for the proposed methods will be discussed, and the performance of the first method will be compared with that of a recently proposed method of Swanpoel and van Wyk, in a Monte Carol study. It is found that, when applied to the problem of estimating the variance of a log spectrum estimate, all methods under consideration can sometimes perform poorly. Overall, the frequency domain method used in conjunction with automatic spectrum estimate choice criterion developed by Hurvich, is found to perform best
A new bootstrap method combined with the stationary bootstrap of Politis and Romano (1994) and the c...
In statistical data analysis it is often important to compare, classify, and cluster di¤erent time s...
We prove that Efron's bootstrap applied to the sample ofstudentized periodogram ordinates works quit...
Abstract. We propose a general bootstrap procedure to approximate the null distri-bution of nonparam...
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...
Bootstrap techniques in the frequency domain have been proved to be effective instruments to approx...
We propose a general bootstrap procedure to approximate the null distribution of nonparametric frequ...
This article presents a simple bootstrap method for time series. The proposedmethod is model-free, ...
International audienceThis paper focuses on the spectral analysis of time series. The samples of the...
We construct bootstrap prediction intervals for linear autoregressions, nonlinear autoregressions, n...
D.Phil.We propose solutions to two statistical problems using the frequency domain approach to time ...
International audienceThe bootstrap is typically less reliable in the context of time-series models ...
We propose a general bootstrap procedure to approximate the null distribution of nonparametric frequ...
In this paper consistency of the Frequency Domain Bootstrap for differentiable functionals of spectr...
A new bootstrap method combined with the stationary bootstrap of Politis and Romano (1994) and the c...
In statistical data analysis it is often important to compare, classify, and cluster di¤erent time s...
We prove that Efron's bootstrap applied to the sample ofstudentized periodogram ordinates works quit...
Abstract. We propose a general bootstrap procedure to approximate the null distri-bution of nonparam...
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...
Bootstrap techniques in the frequency domain have been proved to be effective instruments to approx...
We propose a general bootstrap procedure to approximate the null distribution of nonparametric frequ...
This article presents a simple bootstrap method for time series. The proposedmethod is model-free, ...
International audienceThis paper focuses on the spectral analysis of time series. The samples of the...
We construct bootstrap prediction intervals for linear autoregressions, nonlinear autoregressions, n...
D.Phil.We propose solutions to two statistical problems using the frequency domain approach to time ...
International audienceThe bootstrap is typically less reliable in the context of time-series models ...
We propose a general bootstrap procedure to approximate the null distribution of nonparametric frequ...
In this paper consistency of the Frequency Domain Bootstrap for differentiable functionals of spectr...
A new bootstrap method combined with the stationary bootstrap of Politis and Romano (1994) and the c...
In statistical data analysis it is often important to compare, classify, and cluster di¤erent time s...
We prove that Efron's bootstrap applied to the sample ofstudentized periodogram ordinates works quit...