Parameter Estimation for Exponentially Tempered Power Law Distributions
نویسندگان
چکیده
Tail estimates are developed for power law probability distributions with exponential tempering, using a conditional maximum likelihood approach based on the upper order statistics. Tempered power law distributions are intermediate between heavy power-law tails and Laplace or exponential tails, and are sometimes called “semiheavy” tailed distributions. The estimation method is demonstrated on simulated data from a tempered stable distribution, and for several data sets from geophysics and finance that show a power law probability tail with some tempering.
منابع مشابه
Parameter estimation for tempered power law distributions ∗
Tail estimates are developed for power law probability distributions with exponential tempering using a conditional maximum likelihood approach based on the upper order statistics. The method is demonstrated on simulated data from a tempered stable distribution, and for several data sets from geophysics and finance that show a power law probability tail with some tempering.
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