Statistical Inference for Stable Distribution Using EM algorithm
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The class of α-stable distributions with a wide range of applications in economics, telecommunications, biology, applied, and theoretical physics. This is due to the fact that it possesses both the skewness and heavy tails. Since α-stable distribution suffers from a closed-form expression for density function, finding efficient estimators for its parameters has attracted a great deal of attention in the literature. Here, we propose some EM algorithm to estimate the maximum likelihood estimators of the parameters of α-stable distribution. The performance of the proposed EM algorithm is demonstrated via comparison study in the presence of other well-known competitors and analyzing three sets of real data.
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