@inproceedings{4ce14e87ee7342339de2231a7f7802b0,
title = "Parameter estimation of alpha-stable distributions based on MCMC",
abstract = "The α -stable distribution is a very flexible tool to model NonGaussian data. Stable distributions can allow for modeling infinite variance, skewness and heavy tails, but gives rise to inferential problems related to the estimation of the stable distribution parameters. In this work, we study the estimation of α -stable distributions using numerical Bayesian sampling techniques such as Markov chain Monte Carlo (MCMC), which can simultaneously estimate the four parameters of the model with good performance. Metropolis-Hastings algorithm is used to update the parameters of α -stable distribution at every iteration. The simulation results show that our estimation method is capable of estimating all the parameters accurately.",
keywords = "Alpha Stable distributions, MCMC, Metropolis-Hastings algorithm",
author = "Hao, \{Yan Ling\} and Shan, \{Zhi Ming\} and Feng Shen and Lv, \{Dong Ze\}",
year = "2011",
doi = "10.1109/ICACC.2011.6016424",
language = "英语",
isbn = "9781424488087",
series = "2011 3rd International Conference on Advanced Computer Control, ICACC 2011",
pages = "325--327",
booktitle = "2011 3rd International Conference on Advanced Computer Control, ICACC 2011",
note = "3rd IEEE International Conference on Advanced Computer Control, ICACC 2011 ; Conference date: 18-01-2011 Through 20-01-2011",
}