Total new HIV infections in Togo: a box-jenkins arima approach
Smartson. P. Nyoni, Thabani Nyoni
Abstract
Open-access reader
Smartson. P. Nyoni, Thabani Nyoni
Abstract
Open-access reader
Using annual time series data on the total number of new HIV infections in Togo from 1990 – 2018, the study makes predictions for the period 2019 – 2030. The research applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, J, the series under consideration is an I (2) variable. Based on the AIC, the study presents the ARIMA (0, 2, 2) model as the optimal model. The diagnostic tests further indicate that the presented model is indeed stable and its residuals are not serially correlated and are also normally distributed. The results of the study indicate that the total number of new HIV infections in Togo is projected to decline sharply by 53.5% from the estimated 4791 new infections in 2019 to approximately 2229 new infections by 2030.
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Using annual time series data on the total number of new HIV infections in Togo from 1990 – 2018, the study makes predictions for the period 2019 – 2030. The research applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, J, the series under consideration is an I (2) variable. Based on the AIC, the study presents the ARIMA (0, 2, 2) model as the optimal model. The diagnostic tests further indicate that the presented model is indeed stable and its residuals are not serially correlated and are also normally distributed. The results of the study indicate that the total number of new HIV infections in Togo is projected to decline sharply by 53.5% from the estimated 4791 new infections in 2019 to approximately 2229 new infections by 2030.
Key concepts: Autoregressive integrated moving average, Box–Jenkins, Human immunodeficiency virus (HIV), Statistics, Time series, Series (stratigraphy), Econometrics, Mathematics