Changes in version 0.1.0 (2026-09-12)                  

  - Initial packaged release of kernel-weighted Cox regression (chestr)
    for exploring treatment effect heterogeneity on a biomarker grid.
  - Implements Kish effective-sample-size (ESS) events-per-df safeguard
    (min_events_per_df, default 10). Grid points below the threshold are
    skipped with NA coefficients and flagged via reliable.
  - Exported API: chestr(), plot.chestr() / plot(), chestr_test().
  - Weighting methods: "distance" (default), "square_distance",
    "legacy".
  - Global permutation test of constant treatment effect over biomarker
    space (T_L2, T_MAX) via chestr_test().
  - Vignette chestr-workflow demonstrates the global Cox → chestr → plot
    workflow (and optional permutation test) on simulated survival data.