{"title":"Robust Bayesian Inference of Dynamic Intervention Two-Pieces Normal Autoregressive Process with Local Influence Analysis","authors":"Fatemeh Pooyannik, Zahra Khodadadi","doi":"10.1007/s40995-025-01779-0","DOIUrl":null,"url":null,"abstract":"<div><p>This study’s objective is to introduce a flexible interventional autoregressive process modified based on the random autoregressive coefficient and asymmetric innovations. The transfer function of the proposed process is designed to follow the dynamic step change structure. In interventional analysis, outliers or influential observations have a considerable influence on statistical inference. Hence, we discuss the Bayesian local influence analysis to evaluate the impact of perturbations in response variables, priors, and simultaneous perturbations regarding the Bayes factor assessor. Considering the Markov Chain Monte Carlo samples, the proposed local influences and diagnostic measures can be easily obtained. The real data of the weekly new cases of COVID-19 within the period 2020-03-01 to 2023-12-17 in Greece verifies the effectiveness of the presented methodologies.\n</p></div>","PeriodicalId":600,"journal":{"name":"Iranian Journal of Science and Technology, Transactions A: Science","volume":"49 4","pages":"987 - 1003"},"PeriodicalIF":1.4000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Science and Technology, Transactions A: Science","FirstCategoryId":"4","ListUrlMain":"https://link.springer.com/article/10.1007/s40995-025-01779-0","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This study’s objective is to introduce a flexible interventional autoregressive process modified based on the random autoregressive coefficient and asymmetric innovations. The transfer function of the proposed process is designed to follow the dynamic step change structure. In interventional analysis, outliers or influential observations have a considerable influence on statistical inference. Hence, we discuss the Bayesian local influence analysis to evaluate the impact of perturbations in response variables, priors, and simultaneous perturbations regarding the Bayes factor assessor. Considering the Markov Chain Monte Carlo samples, the proposed local influences and diagnostic measures can be easily obtained. The real data of the weekly new cases of COVID-19 within the period 2020-03-01 to 2023-12-17 in Greece verifies the effectiveness of the presented methodologies.
期刊介绍：
The aim of this journal is to foster the growth of scientific research among Iranian scientists and to provide a medium which brings the fruits of their research to the attention of the world’s scientific community. The journal publishes original research findings – which may be theoretical, experimental or both - reviews, techniques, and comments spanning all subjects in the field of basic sciences, including Physics, Chemistry, Mathematics, Statistics, Biology and Earth Sciences
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