Changes in version 0.2.0 (2026-10-31)                  

  - S3 classes with methods: post_sim() returns an "acpbvar_post",
    sign_restrict() an "acpbvar_signs", collect_irfs() an "acpbvar_irf",
    each with a print() method; summary() on impulse responses gives the
    quantiles by horizon for selected variables and shocks; plot() on
    impulse responses selects panels. The objects remain the documented
    lists and arrays, so existing code is unaffected; subsetting an
    "acpbvar_irf" with [ returns a plain array.
  - collect_irfs() carries variable names (from post_sim()) and shock
    names (from the rows of S) as dimnames.
  - plot_irfs() gains vars and shocks to select panels, ref to overlay a
    second set of responses (dashed median, dotted band), xlab and
    mfrow; with a single shock the panel titles are the variable names.
  - simulate_var_example(): the impact matrix is recentred so that the
    true responses are typical elements of the sign-identified set (same
    signs and persistence as before).
  - Uhlig vignette: the third series is the commodity price index of
    Uhlig (2005), not the CPI (the monetary help page of bsvarSIGNs
    mislabels it); the sample ends in November 2007.

                        Changes in version 0.1.0                        

  - New vignette on real data: the monetary policy shock of Uhlig (2005)
    on the monetary data shipped by bsvarSIGNs (in Suggests), with a
    comparison of impulse responses and timings against bsvarSIGNs.
  - sign_restrict() gains method = c("per_draw", "joint"): the joint
    accept-reject of Chan's replication code (one rotation per posterior
    draw) is available next to the default per-draw search.
  - build_s2() computes the AR(4) residual variances by OLS (mean of
    squared residuals), as in Chan's get_resid_var.m, instead of
    stats::arima().
  - compute_irf() uses the VMA recursion instead of companion-matrix
    powers (identical output, much faster for large n * p).
  - sign_restrict() gains horizons: sign restrictions can be imposed on
    the impulse responses at horizons 0, ..., horizons, with the same
    matrix at every horizon or a 3-d array with one sign matrix per
    horizon.

Initial release (package formerly named samplerChan).

  - Bayesian structural VAR in the A-form of Chan (2022), with the
    asymmetric conjugate (Minnesota-type) prior; own-lag and cross-lag
    tightness chosen by Empirical Bayes on the closed-form marginal
    likelihood.
  - Exact equation-by-equation posterior simulation (independent
    Normal-Inverse-Gamma draws), analytical recovery of the reduced
    form.
  - Sign-restriction identification on the impact matrix following
    Rubio-Ramirez, Waggoner and Zha (2010); impulse responses with
    posterior bands.

Fixes relative to the development version of May 2026:

  - check_sign() now checks every variable under partial identification
    (it previously looped over the number of shocks), and
    sign_restrict() defaults n_id to nrow(S).
  - sign_restrict() records the posterior draws for which no rotation
    was found within max_tries (attribute failed_draws) and warns when
    any.
  - optim_hyper() no longer imposes a discontinuous kappa < 1 penalty;
    post_sim() stores the optimiser convergence code in spec$convergence
    and warns on non-convergence.
  - Added testthat regression tests and a DGP recovery test.
  - All exported functions validate their arguments and stop with an
    informative message (R/validate.R).
  - Posterior quantities (Cholesky factor of the precision, posterior
    mean, inverse-gamma parameters) are computed once per equation; each
    draw is then one rgamma() and one triangular solve. Same draws for
    the same seed, roughly 200x faster for 50 variables and 4 lags.