Estimation of stable distribution parameters from a dependent sample
Statistics Theory
2014-05-05 v1 Statistics Theory
Abstract
Existing methods for the estimation of stable distribution parameters, such as those based on sample quantiles, sample characteristic functions or maximum likelihood generally assume an independent sample. Little attention has been paid to estimation from a dependent sample. In this paper, a method for the estimation of stable distribution parameters from a dependent sample is proposed based on the sample quantiles. The estimates are shown to be asymptotically normal. The asymptotic variance is calculated for stable moving average processes. Simulations from stable moving average processes are used to demonstrate these estimators.
Cite
@article{arxiv.1405.0374,
title = {Estimation of stable distribution parameters from a dependent sample},
author = {Adrian W. Barker},
journal= {arXiv preprint arXiv:1405.0374},
year = {2014}
}
Comments
18 pages, 1 figure. Most of this paper is included in chapter 3 of my PhD thesis, which is yet to be submitted