Computational uncertainty quantification for random time‐discrete epidemiological models using adaptive gPC

DOI10.1002/mma.5315zbMath1406.92557OpenAlexW2897354160MaRDI QIDQ4614555

J. Calatayud, M. Jornet, Rafael-Jacinto Villanueva, Juan-Carlos Cortés

Publication date: 31 January 2019

Published in: Mathematical Methods in the Applied Sciences (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10251/125225

zbMATH Keywords

stochastic difference equationscomputational methods for stochastic equationscomputational uncertainty quantificationadaptive gPCrandom nonlinear difference equations modelrandom population dynamics modelrandom time-discrete epidemiological model

Mathematics Subject Classification ID

Epidemiology (92D30) Population dynamics (general) (92D25) Generalized stochastic processes (60G20) Stochastic functional-differential equations (34K50)

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