چكيده لاتين :
One of the most challenging characteristics of heavy tailed distribution is their high or even infinite variance or burstiness. Heavy-tailed distributions are the distributions, the tails of which cannot be cut off. So, we cannot neglect the large-scale but rare events. The most evident and natural problem of statistical estimation connected with heavy tailed distributions are the problem of their parameter estimation. For estimating their parameter, known statistical procedures can be used, for example, estimation methods of Hill, de Haan and others. This research addresses a new method for estimating the parameters of heavy tailed distributions based on the empirical distribution and, using the list squares method. To demonstrate the ability of the proposed approach, it is applied to famous Parteo and Student distributions as two different examples. The related numerical results are reported.
