Stochastic model construction of observed random phenomena

Abstract A method for constructing probabilistic models of non-stationary time dependent natural hazards is proposed. It is based on the use of Karhunen–Loeve expansion and of a kernel estimator for the distribution of the multivariate random variables appearing in the expansion. The terms of the expansion and the distribution are identified from available measures. The approach is assessed through an academic example and is then applied to seismic ground motion modelling based on recorded data.

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