A statistical approach and analysis computing based on autoregressive integrated moving averages models to predict COVID-19 outbreak in Iraq

Abstract

A time series has been adopted for the numbers of people infected with the Covid-19 pandemic in Iraq for a whole year, starting from the first infection recorded on February 18, 2020 until the end of February 2021, which was collected in the form of weekly observations and at a size of 53 observations. The study found the quality and suitability of the autoregressive moving average model from order (1,3) among a group of autoregressive moving average models. This model was built according to the diagnostic criteria. These criteria are the Akaike information criterion, Bayesian Information Criterion, and Hannan & Quinn Criterion models. The study concluded that this model from order (1,3) is good and appropriate, and its predictions can be adopted in making decisions.