DETERMINATION OF CONCENTRATION OF EARTHQUAKES CLUSTERING

Earthquakes arrive without previous warning and can destroy a whole city in a few seconds, causing numerous deaths and economical losses Nowadays, a great effort is being made to develop techniques that forecast these unpredictable natural disasters by using statistical methods In most studies of earthquake spatial distribution prediction are used statistical estimation of the fractal spatial dimension Earthquake spatial distribution is very complex because of the depth inhomogeneity, the fractal character of spatial pattern, and various hypocenter location errors all make model parameterization difficult and create various biases in estimating parameters However, these publications insufficiently consider the systematic effects which influenced estimation of the fractal or scaling dimensions of earthquakes Some of the above publications estimated several effects by using simulation catalogs; such simulations are insufficient for fully understanding various geometrical distributions In this paper, Copulas methods are used for pattern recognition of earthquake distribution The study of copulas and their applications in statistics is a rather modern phenomenon Copulas are of interest to statisticians for two main reasons: Firstly, as a way of studying scale-free measures of dependence; and secondly, as a starting point for statistical seismicity analysis with a view to simulation earthquake data catalogue

Keywords:

Hazard Assessment , Statistical Pattern Recognition , Clustering , Earthquake Catalog