Stein's method has emerged as a powerful and versatile tool in probability theory for deriving error bounds in distributional approximations. Originally developed to ...

Stein's method has emerged as a critical framework in the study of distributional approximations, providing quantitative bounds between probability distributions through the formulation and solution ...

This is a preview. Log in through your library . Abstract We introduce a variation of the proof for weak approximations that is suitable for studying the densities of stochastic processes which are ...

We develop analytical approximations to bootstrap distribution functions of statistics that are smooth functions of vector means. In particular, our technique is applicable in the case of bootstrap ...