scholarly journals Limiting crossing probabilities of random fields

2006 ◽  
Vol 43 (03) ◽  
pp. 884-891 ◽  
Author(s):  
L. Pereira ◽  
H. Ferreira

Random fields on , with long-range weak dependence for each coordinate individually, usually present clustering of high values. For each one of the eight directions in , we formulate restriction conditions on local occurrence of two or more crossings of high levels. These smooth oscillation conditions enable computation of the extremal index as a clustering measure from the limiting mean number of crossings. In fact, only four directions must be inspected since for opposite directions we find the same local path crossing behaviour and the same limiting mean number of crossings. The general theory is illustrated with several 1-dependent nonstationary random fields.

2006 ◽  
Vol 43 (3) ◽  
pp. 884-891 ◽  
Author(s):  
L. Pereira ◽  
H. Ferreira

Random fields on , with long-range weak dependence for each coordinate individually, usually present clustering of high values. For each one of the eight directions in , we formulate restriction conditions on local occurrence of two or more crossings of high levels. These smooth oscillation conditions enable computation of the extremal index as a clustering measure from the limiting mean number of crossings. In fact, only four directions must be inspected since for opposite directions we find the same local path crossing behaviour and the same limiting mean number of crossings. The general theory is illustrated with several 1-dependent nonstationary random fields.


ROBOT ◽  
2010 ◽  
Vol 32 (3) ◽  
pp. 326-333
Author(s):  
Mingjun WANG ◽  
Jun ZHOU ◽  
Jun TU ◽  
Chengliang LIU

Author(s):  
V. V. Anh ◽  
K. E. Lunney

AbstractThis paper considers a large class of non-stationary random fields which have fractal characteristics and may exhibit long-range dependence. Its motivation comes from a Lipschitz-Holder-type condition in the spectral domain.The paper develops a spectral theory for the random fields, including a spectral decomposition, a covariance representation and a fractal index. From the covariance representation, the covariance function and spectral density of these fields are defined. These concepts are useful in multiscaling analysis of random fields with long-range dependence.


2004 ◽  
Vol 41 (A) ◽  
pp. 35-53 ◽  
Author(s):  
V. V. Anh ◽  
N. N. Leonenko ◽  
L. M. Sakhno

This paper provides a quasi-likelihood or minimum-contrast-type method for the parameter estimation of random fields in the frequency domain based on higher-order information. The estimation technique uses the spectral density of the general kth order and allows for possible long-range dependence in the random fields. To avoid bias due to edge effects, data tapering is incorporated into the method. The suggested minimum contrast functional is linear with respect to the periodogram of kth order, hence kernel estimation for the spectral densities is not needed. Furthermore, discretization is not required in the estimation of continuously observed random fields. The consistency and asymptotic normality of the resulting estimators are established. Illustrative applications of the method to some problems in mathematical finance and signal detection are given.


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