Simulation of Non-Gaussian Correlated Random Variables, Stochastic Processes and Random Fields: Introducing the anySim R-Package for Environmental Applications and Beyond

Numerical Simulation of Non-Gaussian Random Fields

The non-Gaussian random fields are used to modelling some dynamic loads generated by wind turbulence, ocean waves, earthquake ground motion etc. These fields also represent the uncertain properties of different materials (reinforced concrete, composite, soils etc.). This paper presents some methods and the corresponding algorithms to the numerical simulation of stationary non-Gaussian random fi...

Random Variables and Stochastic Processes

Stochastic Processes and Random Fields

Generation of Correlated Non-gaussian Random Variables from Independent Components

Simulations are often needed when the performance of new methods is evaluated. If the method is designed to be blind or robust, simulation studies must cover the whole range of potential random input. It follows that there is a need for advanced tools of data generation. The purpose of this paper is to introduce a technique for the generation of correlated multivariate random data with non-Gaus...

Stochastic relations of random variables and processes

This paper generalizes the notion of stochastic order to a relation between probability measures over arbitrary measurable spaces. This generalization is motivated by the observation that for the stochastic ordering of two stationary Markov processes, it suffices that the generators of the processes preserve some, not necessarily reflexive or transitive, subrelation of the order relation. The m...