NEWS

ROOT 0.2.0

Added positivity_trim argument to ROOT() and characterizing_underrep() for pre-trimming target observations with structural positivity violations prior to optimization. Supports a fixed numeric threshold (e.g., positivity_trim = 0.05) or the data-driven rule of Crump, Hotz, Imbens & Mitnik (2009, Biometrika) via positivity_trim = "crump". Only active in generalizability mode. Trimming metadata is stored in the returned object as positivity_trim_info and reported by summary().
Added split_strategy argument to ROOT() and characterizing_underrep() with options "midpoint" (default, backward-compatible) and "random_quantile". The random quantile strategy draws a uniform random quantile within quantile_range (default 10th–90th percentile) at each split, improving covariate-space coverage across the forest. The strategy used is stored in the returned object and reported by summary().
New internal helpers: crump_alpha(), trim_positivity_violations(), and split_point().

Added roxygen documentation for all new arguments and helper functions.
Added Crump et al. (2009) to @references in ROOT().
summary.ROOT() now reports the split strategy and positivity trimming diagnostics.