under are highly nonstandard due to the inherent irregular natures of the problem, and then construct bootstrap critical …

normality. Bootstrap inference can be expected to be more reliable, and appropriate bootstrap procedures are proposed. As an … enough for asymptotic and bootstrap inference to be almost identical, but that, in the twenty-first century, the bootstrap …

This paper is aimed at presenting application of bootstrap interval estimation methods to the assessment of financial … investment’s effectiveness and risk. At first, we give an overview of various methods of bootstrap confidence interval estimation …, i.e. bootstrap-t interval, percentile interval and BCa interval. Then, bootstrap confidence interval estimation methods …

In this paper, we introduce a method of generating bootstrap samples with unknown patterns of cross …-sectional/spatial dependence, which we call the spatial dependent wild bootstrap. This method is a spatial counterpart to the wild dependent … bootstrap of Shao (2010) and generates data by multiplying a vector of independently and identically distributed external …

-run asymmetry are generally oversized if the threshold parameter is estimated by conditional least squares and show that bootstrap …

compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models …