Heavy tailed distributions are of considerable importance in modelling a wide range of phenomena in finance geology, hydrology, physics, queuing theory and telecommunication.

We develop a new method for estimating unknown tail index for independent and dependent data. Our estimator is based on a variant of statistics sometimes called empirical structure function or partition function.

Joint work with D. Grahovac (Osijek University, Croatia) and M. Taqqu (Boston University, USA).

[1] Grahovac, D. and  Leonenko, N (2014) Detecting multifractal stochastic processes under heavy-tailed effects, Chaos, Solitons, Fractals, 65, 78-89

[2] Grahovac, D., Jia, M.,  Leonenko, N. and  Taufer, E (2105) Asymptotic properties of the partition function and applications in tail index inference of heavy-tailed data. Statistics 49 , no. 6, 1221–1242

[3] Grahovac, D. and  Leonenko, N and Taqqu, M. S. (2015) Scaling properties of the structure function of linear  fractional stable motion and estimation of its parameters, Journal of Statistical Physics, 158, 105-119

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1. Book your nearest ACE facility;

2. Notify the seminar convenor at La Trobe University  (Andriy Olenko) to notify you will be participating.

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