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Analyzing the Gaver - Lewis Pareto Process under an Extremal Perspective
Publication . Ferreira, Marta; Ferreira, Helena
Pareto processes are suitable to model stationary heavy-tailed data. Here, we consider the
auto-regressive Gaver–Lewis Pareto Process and address a study of the tail behavior. We characterize
its local and long-range dependence. We will see that consecutive observations are asymptotically
tail independent, a feature that is often misevaluated by the most common extremal models and
with strong relevance to the tail inference. This also reveals clustering at “penultimate” levels.
Linear correlation may not exist in a heavy-tailed context and an alternative diagnostic tool will
be presented. The derived properties relate to the auto-regressive parameter of the process and
will provide estimators. A comparison of the proposals is conducted through simulation and an
application to a real dataset illustrates the procedure.
Estimating the extremal index through local dependence
Publication . Ferreira, Helena; Ferreira, Marta
The extremal index is an important parameter in the characterization of extreme values of a
stationary sequence. Our new estimation approach for this parameter is based on the extremal
behavior under the local dependence condition D(k)(un). We compare a process satisfying one of
this hierarchy of increasingly weaker local mixing conditions with a process of cycles satisfying the
D(2)(un) condition. We also analyze local dependence within moving maxima processes and derive
a necessary and su cient condition for D(k)(un). In order to evaluate the performance of the proposed
estimators, we apply an empirical diagnostic for local dependence conditions, we conduct a
simulation study and compare with existing methods. An application to a nancial time series is
also presented.
Multidimensional extremal dependence coefficients
Publication . Ferreira, Helena; Ferreira, Marta
Extreme value modeling has been attracting the attention of researchers in diverse areas
such as the environment, engineering, and finance. Multivariate extreme value distributions
are particularly suitable to model the tails of multidimensional phenomena. The
analysis of the dependence among multivariate maxima is useful to evaluate risk. Here
we present new multivariate extreme value models, as well as, coefficients to assess
multivariate extremal dependence.
On shadowing and hyperbolicity for geodesic flows on surfaces
Publication . Bessa, Mario; Dias, João Lopes; Torres, Maria Joana
We prove that the geodesic flow on closed surfaces displays a hyperbolic set if the shadowing property holds C2-robustly on the metric. Similar results are obtained when considering even feeble properties like the weak shadowing and the specification properties. Despite the Hamiltonian nature of the geodesic flow, the arguments in the present paper differ completely from those used in Bessa et al. (2013) for Hamiltonian systems.
On the periodic orbits, shadowing and strong transitivity of continuous flows
Publication . Bessa, Mario; Torres, Maria Joana; Varandas, Paulo
We prove that chaotic flows (i.e. flows that satisfy the shadowing property and have a dense subset of periodic orbits) satisfy a reparametrized gluing orbit property similar to the one introduced in Bomfim and Varandas (2015). In particular, these are strongly transitive in balls of uniform radius. We also prove that the shadowing property for a flow and a generic time-t map, and having a dense subset of periodic orbits hold for a C0-Baire generic subset of Lipschitz vector fields, that generate continuous flows. Similar results also hold for C0-generic homeomorphisms and, in particular, we deduce that chain recurrent classes of C0-generic homeomorphisms have the gluing orbit property.
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Funding agency
Fundação para a Ciência e a Tecnologia
Funding programme
5876
Funding Award Number
UID/MAT/00013/2013