A critical look at directional random walk modeling of sparse fossil data
Through simulations and real data analysis, this paper demonstrates that the Generalized Least Squares (GLS) method outperforms the General Random Walk (GRW) model for inferring directional evolution in sparse fossil data with significant measurement errors, as GRW struggles to reliably estimate step variances and often collapses into deterministic processes.