Theta models for daily pandemic data

Abstract

Forecasting techniques are critical for developing better strategies and making timely judgments. As a result, both epidemiologists and statisticians got interested in anticipating the COVID-19 pandemic, which is why we decided to use theta approaches because of their predictive power. The major goal of this research is to determine which of the statistical Theta-methods is the best appropriate for predicting in the case of Covid 19 for the five nations analyzed. performance in forecasting for the other countries under investigation.These strategies make it possible to assess the past in order to make more accurate forecasts about the future. Predicted trends in a phenomenon over time may aid in planning for potential risks and worst-case scenarios. For the first time, a set of algorithms known as theta models is used to forecast the performance of COVID-19 pandemic data in this study. Then we used data from five countries: the United Kingdom, South Africa, Malaysia, Morocco, and Russia. The results suggest that the traditional theta approach is more accurate for data from the United Kingdom, which has a lot of variability. For the other countries analyzed, however, the dynamic optimized theta model performs better in forecasting.