Ambit Stochastics has emerged as a new field in probability theory during the last decade.
While there are still many open questions and challenges, we think that the time is right to …

​​​​​​​ Turbulence is a major problem facing modern societies. It makes airline
passengers return to their seats and fasten their seatbelts but it also creates drag on the …

The concept of ambit processes is outlined. Such stochastic processes are of interest in
spatio-temporal modelling, and they play a central role in recent studies of velocity fields in …

Abstract In 1941 Kolmogorov and Obukhov postulated the existence of a statistical theory of
turbulence, which allows the computation of statistical quantities that can be simulated and …

Ambit processes are general stochastic processes based on stochastic integrals with
respect to Lévy bases. Due to their flexible structure, they have great potential for providing …

Expressions for (absolute) moments of generalized hyperbolic and normal inverse Gaussian
(NIG) laws are given in terms of moments of the corresponding symmetric laws. For the …

In this paper we demonstrate a recursive method for obtaining the moments of the
generalized hyperbolic distribution. The method is readily programmable for numerical …

In this Letter we investigate the dependency with scale of the empirical probability
distribution functions (PDF) of Elsasser increments using large sets of WIND data (collected …

We consider quasi maximum likelihood (QML) estimation for general non-Gaussian discrete-
time linear state space models and equidistantly observed multivariate Lévy-driven …

Many outputs and outcomes of relevance to public administration research are distributed in
a way that escapes simple statistical descriptives. The field of public administration has …