Environmental Health Time Series Forecasting: A Weekend of Learning and Innovation
Associate Professor Dr. Jason Ng was invited by the National Institute of Health (NIH) to be one of the trainers for the Workshop on Environmental Health Time Series Forecasting, which was successfully conducted over a weekend in November. Organized by the Environmental Health Research Centre, the workshop brought together researchers from the Institute of Medical Research (IMR), NIH to enhance their knowledge and skills in time series forecasting for environmental health applications.
Dr. Jason Ng joined Prof. Kamarul Imran (KIM) and Wan Shakira Rodzlan Hasani as one of the three trainers leading the sessions. His session focused on building a strong foundation in time series data before delving into the forecasting workflow, with a particular emphasis on the AutoRegressive Integrated Moving Average (ARIMA) framework.
This workshop also marked the first time he introduced and implemented the `tsibble` and `fable` packages in R. These packages, which integrate seamlessly with the `tidyverse` ecosystem, offer a robust approach to handling multiple time series data. Their ability to facilitate simultaneous forecasting using multiple models makes them a valuable addition to time series analysis.
Looking ahead, Dr. Jason Ng plans to introduce these R packages in the Time Series Forecasting subject within the BSc (Hons) Statistical Data Modelling program by 2025. This will replace the long-standing `forecast` package, ensuring students are equipped with the latest tools for analyzing complex time series data.
Beyond the technical discussions, the workshop provided an opportunity to learn more about the critical research conducted by IMR in public and environmental health. The exchange of ideas and expertise highlighted the potential for future collaborations, strengthening the link between statistical modeling and real-world health applications.
It was a rewarding experience to engage with such talented researchers, and the trainers look forward to more opportunities to contribute to this important field.
Assoc. Prof. Dr Ng Wei Jian and Dr Ang Siew Ling
School of Mathematical Sciences
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