the classical paradigm, by investigating the best way to estimate bootstrap confidence limits on recreational harvest and …

the monetary sector of Germany are estimated and different bootstrap confidence intervals for impulse responses are … computed and compared. These intervals are subject of a concluding and detailed analysis. It is examined whether the bootstrap …

unter allgemeinen Bedingungen etabliert. Die zweite Methode beruht auf der Bootstrap Resampling-Verfahren. Es ist bewiesen …, dass die Bootstrap-Approximation eine wesentliche Verbesserung ergibt. Der Fall von mehrdimensionalen und diskrete … method is based on the bootstrap resampling method. It is proved that the bootstrap approximation provides a substantial …

, as an alternative to the asymptotic approach, we propose a bootstrap confidence band. The developed theory is helpful for …

The research deals with bootstrap interval estimation of wildlife population sizes frommultiple surveys in the Hluhluwe … using line transect sampling and mark-recapture methodsrespectively. The bootstrap and jackknife procedures were applied … separately to each ofthe datasets. Bootstrap estimates for each of the time point were obtained and theconfidence intervals of …

The bootstrap is a computationally intensive data analysis technique. It is particularly useful for analysing small … datasets, and for estimating the sampling distribution of a statistic when it is intractable. We focus on bootstrap hypothesis … testing of linear models. In this context, at present, various versions of the bootstrap are available, and it is not entirely …

are dependent, such as, modelbased bootstrapping and the wild bootstrap, but the error terms need to be whitened. In this … dissertation, a bootstrap procedure is used to test the hypothesis of no trend for variable stars when the error structure assumes … a particular form. In some cases, the bootstrap to be implemented is preferred over large sample tests in terms of the …