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Combining Polynomial Chaos Expansions and the Random Variable Transformation Technique to Approximate the Density Function of Stochastic Problems, Including Some Epidemiological Models

Calatayud-Gregori, Julia; Chen-Charpentier, Benito M.; Cortés, J.C.; Jornet-Sanz, Marc (MDPI AG, 2019-01)

[EN] In this paper, we deal with computational uncertainty quantification for stochastic models with one random input parameter. The goal of the paper is twofold: First, to approximate the set of probability density functions ...
Do the generalized polynomial chaos and Fröbenius methods retain the statistical moments of random differential equations?

Chen Charpentier, Benito Miguel; Cortés López, Juan Carlos; Romero Bauset, José Vicente; Roselló Ferragud, María Dolores (Elsevier, 2013-05)

The aim of this paper is to explore whether the generalized polynomial chaos (gPC) and random Fröbenius methods preserve the first three statistical moments of random differential equations. There exist exact solutions ...
Improvement of random coefficient differential models of growth of anaerobic photosynthetic bacteria by combining Bayesian inference and gPC

Calatayud, Julia; Cortés, J.-C.; Jornet, Marc (John Wiley & Sons, 2020-09-30)

[EN] The time evolution of microorganisms, such as bacteria, is of great interest in biology. In the article by D. Stanescu et al. [Electronic Transactions on Numerical Analysis, 34, 44-58 (2009)], a logistic model was ...

Mostrando ítems 1-3 de 3