无限方差稳定Gegenbaeur Arfisma模型

Afrika Statistika Pub Date : 2021-07-01 DOI:10.16929/as/2021.2789.184

Filamory Abraham Michael Keita, Ouagninia Hili, Serge-Hippolyte Arnaud Kanga

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引用次数: 0

摘要

本文发展了具有稳定创新点的Gegenbauer自回归分数积分季节移动平均(GARFISMA)过程理论。我们建立了它的因果性和可逆性的条件。这是一个有限参数过程，在金融、水文数据研究等方面表现出高变异性、长记忆、周期性和季节性。我们执行一些模拟来说明流程的行为。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Infinite variance stable Gegenbaeur Arfisma models

This paper develops the theory of the Gegenbauer AutoRegressive Fractionally Integrated Seasonal Moving Average (GARFISMA) process with alpha-stable innovations.We establish its conditions for causality and invertibility. This is a finite parameter process which exhibits high variability, long memory, cyclical, and seasonality in financial, hydrological data studies, and more. We perform some simulations to illustrate the behavior of our process.

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Afrika Statistika

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