Nonparamtric bootstrapping methods may be useful for assessing confidence in a supertree inference. We examined the performance of two supertree bootstrapping methods on four published data sets that ...

Bootstrapping is a widely used statistical learning technique that falls under the broader category of resampling methods. Bootstrapping is typically used in the estimation of various statistics and ...

To present a resampling approach to obtain confidence intervals (CIs) and the empirical distributions for the studentized regression residuals percentiles when used as cutoff points for overweight and ...

This is a preview. Log in through your library . Abstract The operation of resampling from a bootstrap resample, encountered in applications of the double bootstrap, may be viewed as resampling ...

In this paper, the authors refer to the axiomatic theory of risk and investigate the problem of formal verification of the expected shortfall (ES) model based on a sample ES. Recognizing the ...