Average sample number function for Pareto heavy tailed distributions
Summary: The main purpose of this work is shortly to give the average sample number function after a sequential probability ratio test on the index parameter \(\alpha\) of stable densities, which we give a mean of the number of data required to take decision in the case \(1<\alpha<2\). We use the fact that the tails of Levy-stable distributions are asymptotically equivalent to a Pareto law for large data. Stable distributions are a rich class of probability distributions that allow skewness and heavy tails and have many intriguing mathematical properties. The lack of closed formulas for densities and distribution functions for all has been a major drawback to the use of stable distributions by practitioners, but few stable distributions have the analytical formula of their density functions which are Gauss, Levy, and Cauchy.
scientific article; zbMATH DE number 6368334