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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Current algorithms for estimating the parameters of a symmetric alpha-stable ARMA process are either highly non-linear, or assume small MA orders (q 3), or invoke the minimum-phase assumption. We use results from the statistics literature to show that the normalized correlation is well-de ned; we show that the normalized cumulants are also well-behaved. We propose to use the correlation to esti...
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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 s...
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ژورنال
عنوان ژورنال: Risks
سال: 2016
ISSN: 2227-9091
DOI: 10.3390/risks4040043