Statistical Inference in Fractional Poisson Ornstein-Uhlenbeck Process
Statistics Theory
2017-12-15 v1 Statistics Theory
Abstract
In this article, we study the problem of parameter estimation for a discrete Ornstein - Uhlenbeck model driven by Poisson fractional noise. Based on random walk approximation for the noise, we study least squares and maximum likelihood estimators. Thus, asymptotic behaviours of the estimator is carried out, and a simulation study is shown to illustrate our results.
Cite
@article{arxiv.1712.05066,
title = {Statistical Inference in Fractional Poisson Ornstein-Uhlenbeck Process},
author = {Héctor Araya and Natalia Bahamonde and Tania Roa and Soledad Torres},
journal= {arXiv preprint arXiv:1712.05066},
year = {2017}
}
Comments
18 pages, 3 figures, 4 tables