Statistical Inference in Fractional Poisson Ornstein-Uhlenbeck Process

12/14/2017
by   Héctor Araya, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/07/2021

Maximum likelihood estimation for sub-fractional Vasicek model

We investigate the asymptotic properties of maximum likelihood estimator...
research
07/03/2020

Least Squares Estimator for Vasicek Model Driven by Sub-fractional Brownian Processes from Discrete Observations

We study the parameter estimation problem of Vasicek Model driven by sub...
research
06/07/2018

Parameter estimation for fractional Poisson processes

The paper proposes a formal estimation procedure for parameters of the f...
research
03/12/2019

Discrete factor analysis

In this paper, we present a method for factor analysis of discrete data....
research
08/30/2018

Maximum likelihood estimator and its consistency for an (L,1) random walk in a parametric random environment

Consider an (L,1) random walk in an i.i.d. random environment, whose env...
research
08/23/2018

Fractional Risk Process in Insurance

Important models in insurance, for example the Carmér--Lundberg theory a...

Please sign up or login with your details

Forgot password? Click here to reset