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Markovian perturbation, response and fluctuation dissipation theorem

Amir Dembo, Jean-Dominique Deuschel (2010)

Annales de l'I.H.P. Probabilités et statistiques

We consider the Fluctuation Dissipation Theorem (FDT) of statistical physics from a mathematical perspective. We formalize the concept of “linear response function” in the general framework of Markov processes. We show that for processes out of equilibrium it depends not only on the given Markov process X(s) but also on the chosen perturbation of it. We characterize the set of all possible response functions for a given Markov process and show that at equilibrium they all satisfy the FDT. That is,...

Multivariate Markov Families of Copulas

Ludger Overbeck, Wolfgang M. Schmidt (2015)

Dependence Modeling

For the Markov property of a multivariate process, a necessary and suficient condition on the multidimensional copula of the finite-dimensional distributions is given. This establishes that the Markov property is solely a property of the copula, i.e., of the dependence structure. This extends results by Darsow et al. [11] from dimension one to the multivariate case. In addition to the one-dimensional case also the spatial copula between the different dimensions has to be taken into account. Examples...

Norms for copulas.

Darsow, William F., Olsen, Elwood T. (1995)

International Journal of Mathematics and Mathematical Sciences

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