報告題目：A zero-modified geometric INAR(1) model for analyzing count time series with multiple features
報 告 人：康堯 助理教授 西安交通大學
報告時間：2022年12月3日 13:30-14:30
報告地點：騰訊會議ID：117-634-740
或點擊鍊接直接加入會議：https://meeting.tencent.com/dm/ZQNQU2R6GEEZ
校内聯系人：程建華 chengjh@jlu.edu.cn
報告摘要：Zero inflation, zero deflation, overdispersion and underdispersion are commonly encountered in count time series. To better describe these characteristics of counts, this paper introduces a zero-modified geometric INAR(1) model based on the generalized negative binomial thinning operator, which contains dependent zero-inflated geometric counting series. The new model contains the NGINAR(1) model, ZMGINAR(1) model and GNBINAR(1) model with geometric marginals as special cases. Some statistical properties are studied and estimates of the model parameters are derived by the Yule-Walker, conditional least squares and maximum likelihood methods. Asymptotic properties and numerical results of the estimates are also studied. Besides, some test and forecasting problems are addressed. Three real data examples are given to show the flexibility and practicability of the new model.
報告人簡介：康堯，助理教授，現就職于西安交通大學數學與統計學院統計系。主要研究領域包括時間序列分析、保險精算。主持國家自然科學青年基金項目1項，國家博士後科學基金面上項目1項，以第一作者在Test、The Canadian Journal of Statistics等雜志發表(接收)SCI論文7篇。
