4 papers
Generalizing Laplace's method by means of Mellin transforms
Henrik Kaiser
A well-known procedure for the asymptotic evaluation of Laplace transforms is Laplace's method. Despite its wide applicability, however, it is easy to find relevant examples where…
Deconvolution of distribution functions without integral transforms
Henrik Kaiser
We study the recovery of the distribution function of a random variable that is subject to an independent additive random error . To be precise, it is assume…
Mean and quantile regression in the copula setting: properties, sharp bounds and a note on estimation
Henrik Kaiser, Wolfgang Trutschnig
Driven by the interest on how uniformity of marginal distributions propa\-gates to properties of regression functions, in this contribution we tackle the following questions: Given…
Deconvolution of arbitrary distribution functions and densities
Henrik Kaiser
In this article we propose a novel approach for the deconvolution of the distribution function associated with an arbitrary probability measure (and possibly existing density). We…