الثلاثاء , يونيو 25 2024

Predicting the number of people recovering from the coronavirus in the State of Libya by using the Box and Jenkins methodology

التنبؤ بأعداد المتعافين من فيروس كورونا في دولة ليبيا باستخدام منهجية بوكس وجينكنز

The time series is considered as one of the most important tools to investigate the microorganisms infection and interpretation their behavior through a specific period of time. This research aims to determine the most efficient statistical model by applying the Box and Jenkins methodology to predict the number of people recovering from the Corona virus in the State of Libya, for developing plans, measures and necessary precautions. The proposed model was compared with several different models using the indicators of the average absolute error and the average relative absolute error. It was found, that the optimal model is a model (0,1, 1), due to passing the stage of examination and diagnosis, and accordingly, this model could be used to predict the independent values for the period (2/11/2022) until (4/11/2002(.

Keywords: Time Series, Box-Jenkins Models, Mean Absolute Error, Mean Absolute Percentage Error, Bayesian Index.

Ahmed AZIZ, Professor, Department of Statistics, College of Science, Al-Marqab University, Al-Khums – LIBYA

Ababkr ALGAFOD, Professor, Faculty Member (PhD), Department of Statistics, Faculty of Science, Al Asmariya University, Zliten – LIBYA

Ababkr ALHWELL, Faculty Member (Master) Assistant Lecturer 3 Department of Statistics, College of Science, Al-Marqab University, Al-Khums – LIBYA

تقييم المستخدمون: كن أول المصوتون !

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