Order shrinkage and selection for the INGARCH(p,q)model

作     者：Yuan Tian Dehui Wang Xinyang Wang 

作者机构：Mathematics School of Jilin University Changchun 130012P.R.China School of EconomicsLiaoning University Shenyang 110036P.R.China School of Mathematics and Systematic Sciences Shenyang Normal University Shenyang 110034P.R.China 

出 版 物：《International Journal of Biomathematics》 (生物数学学报（英文版）)

年 卷 期：2021年第14卷第5期

页      面：295-309页

核心收录：

学科分类：1004[医学-公共卫生与预防医学(可授医学、理学学位)] 100401[医学-流行病与卫生统计学] 10[医学] 

基　　金：Program for Changbaishan Scholars of Jilin Province, (2015010) Natural Science Foundation of Jilin Province, (20180101216JC) National Natural Science Foundation of China, NSFC, (11731015, 11871028, 11901053) 

主　　题：INGARCH(p,q)model penalized conditional maximum likelihood oracle properties epidemiology 

摘      要：The integer-valued generalized autoregressive conditional heteroskedastic(INGARCH)model is often utilized to describe data in biostatistics,such as the number of people infected with dengue fever,daily epileptic seizure counts of an epileptic patient and the number of cases of campylobacterosis infections,*** the structure of such data is generally high-order and sparse,studies about order shrinkage and selection for the model attract many *** this paper,we propose a penalized conditional maximum likelihood(PCML)method to solve this *** PCML method can effectively select significant orders and estimate the parameters,*** simulations and a real data analysis are carried out to illustrate the usefulness of our method.