Changes in version 0.2.0                        

  - Added a glmmTMB model backend for Gaussian (identity-link) models
    #19. All broad- and narrow-sense estimators (H2_*() / h2_*(),
    including Standard, Cullis, Oakey, Piepho, and Delta) are supported
    and reproduce the lme4 backend exactly. Non-Gaussian glmmTMB models
    fail with an informative error.
  - Added reliability (r², the coefficient of determination) as an
    additional metric #24. h2_Reliability() / H2_Reliability() return
    the overall (mean) reliability r̄², h2_Reliability_by_genotype() /
    H2_Reliability_by_genotype() return the per-genotype values, and
    H2_Reliability_parameters() computes them from variance components.
    The measure is also available via h2(method = "Reliability") and
    H2(method = "Reliability") (not part of the default method set).
  - h2() and H2() now fail with an informative error for non-Gaussian
    lme4 models (e.g. glmer()) instead of a cryptic method-dispatch
    error #48.
  - Added narrow-sense heritability estimation through h2() and the
    h2_*() estimator functions for models with a known additive genetic
    covariance structure.
  - Added a consistent interface across broad-sense (H2()), narrow-sense
    (h2()), and their Standard, Cullis, Oakey, Piepho, and Delta
    estimators.
  - Added support for more complex asreml and lme4 random-effect
    structures, including known genomic relationship matrices and
    structured residuals.
  - Added richer heritable objects that retain the fitted model and
    calculation metadata for downstream methods.

                        Changes in version 0.1.1                        

  - Update Maintainer to Dr. Emi Tanaka
  - Refactored asreml integration #37, #32
      - Added var_comp.asreml() for extracting and assembling variance
        components for asreml model objects
  - Refactored H2() for asremlmodels so that it now takes arguments like
    marginal, stratification
      - Improved handling of vm() specification
  - Refactored H2_standard()
  - Compute confidence intervals for heritable objects #30