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math.ST2025
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…
math.ST2025
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…
math.ST2025
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…