On estimating extremal dependence structures by parametric spectral measures

Towards Estimating Extremal Serial Dependence via the Bootstrapped Extremogram

Davis and Mikosch [3] introduced the extremogram as a flexible quantitative tool for measuring various types of extremal dependence in a stationary time series. There we showed some standard statistical properties of the sample extremogram. A major difficulty was the construction of credible confidence bands for the extremogram. In this paper, we employ the stationary bootstrap to overcome this...

the effect of consciousness-raising activities on learning grammatical structures by iranian guidance school efl learners

abstract the first purpose of this study was to investigate the effect of consciousness-raising (c-r) activities on learning grammatical structures (simple present tense in this case) by iranian guidance school efl learners. the second one was to investigate the effect of gender on learning the simple present tense through c-r activities and tasks. finally, this study aimed to investigate the ...

On extremal dependence of block vectors

On Extremal Measures for Conservative Particle Systems

– It is well known that the exclusion, zero-range and misanthrope particle systems possess families of invariant measures due to the mass conservation property. Although these families have been classified a great deal, a full characterization of their extreme points is not available. In this article, we consider an approach to the study of this classification. One of the results in this note i...

Parametric spectral correlations in disordered and chaotic structures.

We explore the influence of external perturbations on the energy levels of a Hamiltonian drawn at random from the Gaussian unitary distribution of Hermitian matrices. By deriving the joint distribution function of eigenvalues, we obtain the (n,m)-point parametric correlation function of the initial and the final density of states for perturbations of arbitrary rank and strength. A further gener...