Abstract
Modeling COVID-19 cases using count data approach has been scarce in the Philippine setting. This study compares the NB-INGARCH with the traditional ARIMA in modeling daily COVID-19 cases in Iligan City (August 14, 2020 – October 31, 2021). We employ the maximum likelihood estimation method and compare the models using the Akaike's information criterion (AIC). Empirical results reveal that the NB-INGARCH(7,0) outperforms ARIMA(2,1,3) in terms of forecast evaluation measures. However, the results show that rainfall and air pressure have no significant effects on the cases. We conclude that the NB-INGARCH model is a viable alternative approach to modeling count time series.
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