Changes in version 0.3.1                        

Bug fixes

  - summary() printouts for HMM and multilevel fits now include the
    marginal scale/shape parameters (e.g. sigma_exp, omega, delta,
    sigma_gam, shape_gam) for non-normal and per-variable (mixed)
    margins. Previously the HMM summary omitted all margin scale
    parameters, and the multilevel summary dropped them for mixed
    margins.
  - simulate_breakpoint_data() now records the breakpoint specification
    (type, plus breakpoint or breakpoints) in true_params, so the
    documented access no longer returns NULL.

Validation

  - rho_decreasing() and rho_increasing() now validate that rho_start
    and rho_end are single finite values in [-1, 1], matching the other
    rho trajectory generators.

Documentation

  - Extensive roxygen, vignette, README, and CITATION updates so the
    documentation reflects per-variable (mixed) margin support across
    all model families (including the Clayton-copula constant model) and
    the correct coef() / fitted() / data-preparation contracts.

Internal

  - Removed unused helper code, made the exponential-margin diagnostic
    generated quantity (b_gq) report the clamped lower bound
    consistently across the exponential models (inference-neutral), and
    corrected Stan prior-hyperparameter comments. The Clayton-normal
    constant model's sigma_eps prior is left unchanged and its
    intentional divergence from the other constant models is now
    documented.

                        Changes in version 0.3.0                        

Per-variable (mixed) margins

  - All copula VAR model families now accept a length-2 margins vector
    so each variable can use its own marginal family, e.g. margins =
    c("normal", "exponential"). This exploits the copula's separation of
    the marginal distributions from the dependence structure. Supported
    across dcvar_constant(), dcvar(), dcvar_hmm(), dcvar_multilevel(),
    and dcvar_sem() (both the indicator and naive methods).
  - Added generic mixed-margins Stan models that dispatch each dimension
    to its own marginal family and apply the copula on the CDF scale:
    constant_mixed.stan, dcvar_mixed_ncp.stan, hmm_mixed.stan,
    multilevel_mixed.stan, sem_mixed.stan, and sem_naive_mixed.stan.
  - Mixed margins are also available with the Clayton copula for the
    constant model (constant_mixed_clayton.stan), previously limited to
    normal margins.
  - simulate_dcvar(), simulate_dcvar_multilevel(), and
    simulate_dcvar_sem() accept the same per-variable margins vector so
    mixed-family data can be generated (for example for
    parameter-recovery studies).
  - coef(), var_params(), pit_values(), and the diagnostics/plots report
    each dimension under its own family for mixed fits across all model
    families.

Backward compatibility

  - A single margins string is unchanged, and an all-identical margins
    vector (such as c("normal", "normal")) routes to the existing
    specialised single-family model, so prior results, tests, and the
    gamma shared-shape parameterisation are preserved exactly.
  - The mixed multilevel and SEM models support all four families per
    dimension. Single-family multilevel and SEM fits keep their existing
    normal/exponential-only restriction (there is no specialised gamma
    or skew-normal model for those structures); request the other
    families through a per-variable margins vector instead.

                 Changes in version 0.2.0 (2026-04-27)                  

Simulation model parity

  - Added a constant Clayton-copula DC-VAR for normal margins via
    dcvar_constant(copula = "clayton").
  - Added exponential-margin support for dcvar_multilevel().
  - Added naive SEM score models via dcvar_sem(method = "naive") for
    normal and exponential margins.
  - Added dependence_summary() for Kendall's tau summaries across
    Gaussian and Clayton copula fits.

Infrastructure

  - Added copula-family dispatch alongside the existing margin dispatch.
  - Added bundled Stan models for the new Clayton, multilevel
    exponential, and naive SEM variants.
  - Updated extractors, summaries, diagnostics, LOO support, and tests
    for the new model variants.

                 Changes in version 0.1.0 (2026-04-22)                  

Scope and documentation

  - Clarified that the package currently implements Gaussian-copula
    models only.
  - Marked the multilevel and SEM variants as experimental extensions
    with narrower diagnostic support than the core single-level models.
  - Documented PIT diagnostics as posterior-mean plug-in diagnostics and
    made the unsupported multilevel and SEM paths explicit in the help
    pages.
  - Clarified the current scope of loo() support across model classes.

Build and submission hygiene

  - Excluded local *-test-local.log artifacts from source builds.
  - Added package citation metadata.

Testing

  - Added skew-normal fit coverage for dcvar() and dcvar_hmm().
  - Added PIT smoke coverage for gamma and skew-normal margins.