accounted for by constructing confidence intervals based on resampling. Finally, as an alternative approach to including the …

bootstrap. Standard resampling techniques and a new method for nonparametric resampling under the null hypothesis are discussed …. Monte-Carlo simulations show that some bootstrap methods outperform the commonly used normal approximation while other … bootstrap methods—including those which are used in most empirical applications—are hardly any better. Copyright Springer …

series, completed with a bootstrap spectral analysis. The DFA provides a quantitative measure of predictability by computing …

accounted for by constructing confidence intervals based on resampling. Finally, as an alternative approach to including the …

This paper proposes several resampling algorithms suitable for error component models and evaluates them in the context … of bootstrap testing. In short, all the algorithms work well and lead to tests with correct or close to correct size …. There is thus little or no reason not to use the bootstrap with error component models. …

methods and compared their performance in terms of empirical coverage and width. We developed a bootstrap case cross …-validation (BCCV) resampling scheme and defined several confidence interval methods using BCCV with and without bias-correction. The … the literature tend to give overly conservative confidence intervals. Using BCCV resampling, the percentile confidence …