Network-Guided Temporal Forests for Feature Selection in High- Dimensional Longitudinal Data // Implements the Temporal Forest algorithm for feature selection in high-dimensional longitudinal data. The method combines time-aware network construction via weighted gene co-expression network analysis (WGCNA), module-based feature screening, and stability selection using tree-based models. This package provides tools for reproducible longitudinal analysis, closely following the methodology described in Shao, Moore, and Ramirez (2025) https://github.com/SisiShao/TemporalForest.