Parameter estimation for a discrete time model driven by fractional Poisson process

Araya, Hector; Bahamonde, Natalia; Roa, Tania; Torres, Soledad

Abstract

In this article, we study the parametric problem of estimating the coefficient for a discrete time model driven by a fractional Poisson noise, when high-frequency observations are given. We consider weighted least squares and maximum likelihood estimators. Thus, asymptotic behavior of the estimators is proved and a simulation study is shown to illustrate our results.

Más información

Título según WOS: Parameter estimation for a discrete time model driven by fractional Poisson process
Título de la Revista: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Editorial: TAYLOR & FRANCIS INC
Fecha de publicación: 2021
DOI:

10.1080/03610926.2021.1973504

Notas: ISI