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Una generalización de los procesos estocásticos log-normal y de Gompertz como procesos de Itô.

Juan Gómez García, Fulgencio Buendía Moya (2001)

Qüestiió

Estudiamos una ecuación diferencial estocástica de Itô que es una generalización de los modelos estocásticos logarítmico-normal y de Gomperz. Reducimos la ecuación mediante una transformación de cambio de estado a otra que resulta una generalización de la ecuación de Langevin, que rige el proceso de Uhlenbeck-Ornstein. A partir de la expresión analítica de las soluciones de ésta y de la original estudiamos las características estadísticas de ambos procesos solución, en particular los momentos de...

Uncertainty orders on the sublinear expectation space

Dejian Tian, Long Jiang (2016)

Open Mathematics

In this paper, we introduce some definitions of uncertainty orders for random vectors in a sublinear expectation space. We all know that, under some continuity conditions, each sublinear expectation 𝔼 has a robust representation as the supremum of a family of probability measures. We describe uncertainty orders from two different viewpoints. One is from sublinear operator viewpoint. After giving definitions such as monotonic orders, convex orders and increasing convex orders, we use these uncertainty...

Uncertainty quantification for data assimilation in a steady incompressible Navier-Stokes problem

Marta D’Elia, Alessandro Veneziani (2013)

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

The reliable and effective assimilation of measurements and numerical simulations in engineering applications involving computational fluid dynamics is an emerging problem as soon as new devices provide more data. In this paper we are mainly driven by hemodynamics applications, a field where the progressive increment of measures and numerical tools makes this problem particularly up-to-date. We adopt a Bayesian approach to the inclusion of noisy data in the incompressible steady Navier-Stokes equations...

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