Parameter estimation for a discrete time model driven by fractional Poisson process. Issue 10 (19th May 2023)

• Record Type: Journal Article
• Authors: Araya, Héctor; Bahamonde, Natalia; Roa, Tania; Torres, Soledad
• Is Part Of: Communications in statistics. Volume 52:Issue 10(2023)
• Page Start: 3452
• Page End: 3477
• Publication Date: 2023-05-19
• Subjects: Fractional Poisson process -- long memory -- weighted least square estimator -- maximum likelihood estimator; 62M09 -- 62F10 -- 62F12; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2021.1973504
• Languages: English
• ISSNs: 0361-0926

Abstract

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.