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Python code implements a rolling-origin forecasting approach for Google Community Mobility Reports data in Thailand. The work applies Facebook Prophet, ARIMA, and Feature Engineered XGBoost models to forecast mobility trends across six location categories during the COVID-19 pandemic. The study includes a Granger Causality Test to examine relationships between mobility patterns and COVID-19 case numbers.
This is a code repository (TXT file), not a dataset of mobility metrics. Users must obtain the actual Google mobility data and COVID-19 case data independently to run the analysis.