Dharini Pathmanathan

In the Model Evaluation subsection of the Methodology, the equation presented for the coefficient of determinationis incorrect. Please view the complete, correct equation here: Reference 1. Azman S, Pathmanathan D, Balakrishnan V. A two-stage forecasting model using random forest subset-based feature selection and BiGRU with attention mechanism: Application to stock indices. PLoS One. 2025;20(5):e0323015.

Abstract Mortality forecasting plays a central role in both demographic and actuarial studies. Classical approaches, such as the Lee-Carter (LC) model, typically rely on mortality rates as the primary measure. In recent years, compositional data analysis (CoDA), which respects summability and non-negativity constraints, has gained increasing attention for mortality forecasting.

4. Results and Discussions 4.1. Stationarity in Time and Space From both spatial and temporal perspectives, stationarity indicates whether the data have constant mean and variance in each location or time. It is important for the space and time variables to be stabilized before applying PCA. Daily closing prices of each stock were converted into daily logarithmic returns using ln p t − ln p t − 1 , where p t is the closing price at time t .