Factorial Difference-in-Differences // Implements the factorial difference-in-differences (FDID) framework for panel data settings where all units are exposed to a universal event but vary in a baseline factor G. Provides support for various estimators; supports robust, bootstrap, and jackknife variance; returns dynamic, pre/event/post aggregates and raw means; and includes helpers for data preparation and plotting. Methodology follows Xu, Zhao and Ding (2026) doi:10.1080/01621459.2026.2628343.