Changes in version 0.1.1 (2026-10-16)                  

  - Add Santosh Patil as a package author for substantial R programming
    and coding contribution. Ashutosh Sawarkar remains the sole
    maintainer.
  - Update the maintainer email and add author contact and ORCID
    metadata.
  - Metadata-only release; no statistical, API, or package behaviour
    changes.

                        Changes in version 0.1.0                        

First research release

  - Freeze the seven-function research API for externally supplied
    prediction means and full joint prediction-error covariance.
  - Provide M0--M3 comparison, expected selected-set reliability,
    candidate-level advancement probabilities, and the relative
    uncertainty diagnostic Omega(H).
  - Add geometric target-environment support diagnostics and an H-curve
    workflow.
  - Clarify assumptions, fixed-k interpretation, Monte Carlo error, RNG
    behavior, candidate-major covariance ordering, and the limits of
    geometric support.
  - Retain the simulated maize data and add a reproducible
    methods/empirical validation vignette. No G2F raw data are included.
  - External evidence: 2024 validation and forward year-held-out 2022
    replication found poor absolute calibration, M2 worst, a small M3
    Brier advantage over M1, and overpredicted selected-set reliability.
    The corrected L3a 2022 baseline is canonical; the original
    denominator error and correction are retained in the separate audit
    archive.

Known limitations: probabilities are conditional on the supplied
upstream predictive distribution and target-environment specification.
Empirical calibration is poor in the two validation settings; software
release readiness does not imply calibrated probabilities or guaranteed
genetic gain.

                        Changes in version 0.0.3                        

  - Added br_compare() and br_curve() as wrappers around the unchanged
    H2 core.
  - Added range and standardized nearest-environment support
    diagnostics.
  - Added compact S3 print, summary and plot methods for the new result
    classes.
  - Added entirely simulated maize data, a reproducible generation
    script, and an executable end-to-end vignette with explicit
    fit-import and calibration limits.
  - Added executable examples to all principal public functions and
    regression tests.
  - Clarified expected-fraction set reliability, Monte Carlo limitations
    and fixed TPE assumptions. No core mathematics or H2 tests were
    changed.