دانشگاه علامه طباطبایی

  اخبار و اعلانات

 آمار

تعداد نشریات60
تعداد شماره‌ها2,185
تعداد مقالات17,683
تعداد مشاهده مقاله54,292,897
تعداد دریافت فایل اصل مقاله28,418,381
Mahmoodi, Manijeh, Salehi Rad, Mohammad Reza, Eskandari, Farzad. (1402). The vector autoregressive model with asymmetric shocks for the new cases and the new deaths of Covid-19 in Iran. سامانه مدیریت نشریات علمی, 2(1), 79-93. doi: 10.22054/jdsm.2024.78857.1044
Manijeh Mahmoodi; Mohammad Reza Salehi Rad; Farzad Eskandari. "The vector autoregressive model with asymmetric shocks for the new cases and the new deaths of Covid-19 in Iran". سامانه مدیریت نشریات علمی, 2, 1, 1402, 79-93. doi: 10.22054/jdsm.2024.78857.1044
Mahmoodi, Manijeh, Salehi Rad, Mohammad Reza, Eskandari, Farzad. (1402). 'The vector autoregressive model with asymmetric shocks for the new cases and the new deaths of Covid-19 in Iran', سامانه مدیریت نشریات علمی, 2(1), pp. 79-93. doi: 10.22054/jdsm.2024.78857.1044
Mahmoodi, Manijeh, Salehi Rad, Mohammad Reza, Eskandari, Farzad. The vector autoregressive model with asymmetric shocks for the new cases and the new deaths of Covid-19 in Iran. سامانه مدیریت نشریات علمی, 1402; 2(1): 79-93. doi: 10.22054/jdsm.2024.78857.1044

The vector autoregressive model with asymmetric shocks for the new cases and the new deaths of Covid-19 in Iran

Journal of Data Science and Modeling
دوره 2، شماره 1 - شماره پیاپی 3، اسفند 2023، صفحه 79-93    اصل مقاله (764.66 K)
نوع مقاله: original
شناسه دیجیتال (DOI): 10.22054/jdsm.2024.78857.1044
نویسندگان
Manijeh Mahmoodi* 1؛ Mohammad Reza Salehi Rad2؛ Farzad Eskandari3
1Department of Statistics, Faculty of Statistics, Mathematics and Computer science, Allameh Tabataba'i University, Tehran, Iran
2Department of Statistics, Faculty of Statistics, Mathematics and Computer science, Allameh Tabataba'i University, Tehran, Iran.
3Department of Statistics Allameh Tabataba'i University
چکیده
Abstract
The novel corona virus (covid-19) spread quickly from person to another and one of the basic aspects of the country management has been to prevent the spread of this disease. So the prediction of its expansion is very important. In such matters, the estimation of new cases and deaths in covid-19 has been considered by researchers. we propose an estimation of the statistical model for predicting the new cases and the new deaths by using the vector autoregressive (VAR) model with the multivariate skew normal (MSN) distribution for the asymmetric shocks and predict the samples data. The maximum likelihood (ML) method is applied to estimation of this model for the weekly data of the new cases and the new deaths of covid-19. Data are taken from World Health Organization (WHO) from March 2020 until March 2023 Iran country. The performance of the model is evaluated with the Akaike and the Bayesian information criterions and the mean absolute prediction error (MAPE) is interpreted.
کلیدواژه‌ها
Covid19؛ Forecasting؛ Maximum likelihood estimation؛ Multivariate skew normal؛ Skewness؛ Vector autoregressive
آمار
تعداد مشاهده مقاله: 234
تعداد دریافت فایل اصل مقاله: 208


login