A least square-type procedure for parameter estimation in stochastic differential equations with additive fractional noise
Probability
2011-11-10 v1 Statistics Theory
Statistics Theory
Abstract
We study a least square-type estimator for an unknown parameter in the drift coefficient of a stochastic differential equation with additive fractional noise of Hurst parameter H>1/2. The estimator is based on discrete time observations of the stochastic differential equation, and using tools from ergodic theory and stochastic analysis we derive its strong consistency.
Keywords
Cite
@article{arxiv.1111.1816,
title = {A least square-type procedure for parameter estimation in stochastic differential equations with additive fractional noise},
author = {Andreas Neuenkirch and Samy Tindel},
journal= {arXiv preprint arXiv:1111.1816},
year = {2011}
}
Comments
15 pages