Controlled Drift Estimation in the Mixed Fractional Ornestein-Uhlenbeck Process

09/08/2020
by   Chunhao Cai, et al.
0

This paper is devoted to the determination of the asymptotical optimal input for the estimation of the drift parameter in a Directly observed but controlled fractional Ornstein-Uhlenbeck process. Large sample asymptotical properties of the Maximum Likelihood Estimator is deduced using the Laplace transform computations.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/30/2020

Maximum likelihood estimator for mixed fractional Vasicek process

In this paper, we will study asymptotical properties of the unknown para...
research
03/30/2020

Maximum likelihood estimation for mixed fractional Vasicek processes

The mixed fractional Vasicek model, which is an extended model of the tr...
research
06/21/2018

Sharp large deviations for the drift parameter of the explosive Cox-Ingersoll-Ross process

We consider a non-stationary Cox-Ingersoll-Ross process. We establish a ...
research
10/26/2017

Optimal Input Design for Parameter Estimation in AR(1) with Dependent Stationary Noise

This paper focus on the asymptotical input and the asymptotical properti...
research
11/25/2019

Drift Estimation for a Lévy-Driven Ornstein-Uhlenbeck Process with Heavy Tails

We consider the problem of estimation of the drift parameter of an ergod...
research
12/03/2019

Statistical inference for fractional diffusion process with random effects at discrete observations

This paper deals with the problem of inference associated with linear fr...
research
03/02/2020

A Fractional Hawkes process

We modify ETAS models by replacing the Pareto-like kernel proposed by Og...

Please sign up or login with your details

Forgot password? Click here to reset