The Prediction by using Nonlinear Autoregressive Model - Salim M. Ahmad; Anas Youns; Ammar Saad Abduljabbar (Statistics, Optimization & Information Computing, 2026)
The study introduced a non-linear autoregressive model with stability conditions of it. This model was employed to Prediction the daily count of new Covid-19 infections in the Kingdom of Saudi Arabia for the year 2022 which the primary aim of this paper. A suggested autoregressive model was introduced, and the stability criteria for this model were identified. The model outlined in the research comprises two components: a linear component and a non-linear component, the latter incorporating a decreasing function. This feature enabled us to get a numerical example that satisfy the theoretically stability criteria that were found, as demonstrated in Example 1 of the study. The suggested model was employed on real data the time series of daily new Covid-19 infections in the Kingdom of Saudi Arabia throughout an uninterrupted three-month period in 2022. Utilizing a Python program, we calculated the values of the model's parameter constants to satisfy the stability conditions. We verified the residuals and utilized the model to predict the anticipated number of new Covid-19 infections for the next month in 2022.