1403/01/09
مهرناز محمدپور

مهرناز محمدپور

مرتبه علمی: دانشیار
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده علوم ریاضی
نشانی:
تلفن: 011-35302475

مشخصات پژوهش

عنوان
Alternative procedures in dependent counting INAR process with application on COVID-19
نوع پژوهش
JournalPaper
کلیدواژه‌ها
Bayesian forecasting; Dependent thinning operator; INAR model; Modified maximum empirical likelihood; Quasi-likelihood
سال
2022
مجله COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
شناسه DOI
پژوهشگران Nisreen Shamma ، Mehrnaz Mohammadpour

چکیده

Alternative estimation and forecasting procedures for the integer-valued autoregressive process with dependent geometric counting series are investigated. Some nonparametric estimation methods are applied to estimate the parameters of the model. The performance of the estimators is assessed via simulation study. We investigate an application of the process using COVID-19 data set and illustrate the best performance of the proposed model among some competitive INAR(1) models via the residual analysis and model adequacy. Consequently, the selected model is applied to predict the number of cases of COVID-19 based on the classic and Bayesian approaches.