Changes in version 1.0.0 (2026-04-02)                  

Major release: complete DSGE estimation and analysis toolkit

Model-implied covariance reporting (v0.10.0)

  - New model_covariance() for unconditional covariance and correlation
    matrices of model observables and controls.
  - Supports ML fits, Bayesian fits, and raw solution objects.

Prediction and reporting tools (v0.10.0)

  - New prediction_interval() for one-step-ahead prediction bands using
    Kalman filter innovation variance.
  - New prediction_accuracy() for RMSE, MAE, and mean bias statistics.
  - Enhanced fitted() method for ML-estimated models.

Robust standard errors (v0.10.0)

  - New robust_vcov() for sandwich (Huber-White) variance-covariance
    estimation. Provides standard errors robust to model
    misspecification.

Bayesian diagnostics and model comparison (v0.10.0)

  - New posterior_predictive() for posterior predictive checks with
    variance and autocorrelation statistics.
  - New marginal_likelihood() via modified harmonic mean estimator for
    Bayesian model comparison.
  - New geweke_test() for Geweke (1992) convergence diagnostic.
  - New mcmc_diagnostics() for comprehensive MCMC health summary.

                        Changes in version 0.9.0                        

Occasionally binding constraints

  - New simulate_occbin() for piecewise-linear simulation under
    inequality constraints (e.g., zero lower bound).
  - New obc_constraint() helper for constraint specification.
  - Shadow-shock algorithm with iterative regime detection.
  - Plot method with constraint-binding period shading.

                        Changes in version 0.8.0                        

Second-order perturbation

  - solve_dsge() now accepts order = 2 for second-order approximation of
    nonlinear models.
  - New simulate_2nd_order() for pruned second-order simulation.
  - New irf_2nd_order() for generalised impulse-response functions with
    asymmetric shock effects.
  - Risk/precautionary corrections to the steady state
    (sigma-correction).

                        Changes in version 0.7.0                        

Perfect foresight / deterministic transition paths

  - New perfect_foresight() for deterministic simulation of transition
    paths after temporary or permanent shocks.
  - Supports both linear and linearized nonlinear models.
  - Plot method with deviation-from-steady-state and level views.

                        Changes in version 0.6.0                        

Identification and sensitivity analysis

  - New check_identification() for local identification diagnostics via
    Jacobian SVD of the autocovariance mapping.
  - New parameter_sensitivity() for sensitivity of likelihood, IRFs,
    steady state, and policy matrices to parameter perturbations.
  - New prior_posterior_update() for Bayesian informativeness
    diagnostics comparing posterior concentration to prior width.

                        Changes in version 0.5.0                        

Kalman smoother and shock decomposition

  - New smooth_states() for Rauch-Tung-Striebel Kalman smoothing.
  - New smooth_shocks() for extraction of smoothed structural shocks.
  - New shock_decomposition() for historical decomposition of observed
    variables into individual shock contributions.
  - Plot methods for smoothed states and shock decomposition.

                        Changes in version 0.4.0                        

Bayesian nonlinear DSGE estimation

  - bayes_dsge() now accepts dsgenl_model objects for Bayesian
    estimation of nonlinear DSGE models via first-order perturbation.
  - For each MCMC draw, the model's steady state is re-solved and the
    system re-linearized at the candidate parameters, ensuring correct
    parameter- dependent dynamics.
  - Failed steady-state solves, linearization failures, and
    Blanchard-Kahn violations are handled gracefully --- proposals are
    rejected without crashing the sampler. Failure counts are reported
    in the output.
  - Data is automatically centered around the parameter-specific steady
    state for nonlinear models.
  - Posterior IRFs work for nonlinear models via the same irf()
    interface.

                        Changes in version 0.3.0                        

Bayesian estimation (linear)

  - New bayes_dsge() function for Bayesian estimation of linear DSGE
    models via adaptive Random-Walk Metropolis-Hastings (RWMH).
  - New prior() constructor for specifying prior distributions: normal,
    beta, gamma, uniform, and inv_gamma.
  - Multiple chains with dispersed starting points from prior draws.
  - Adaptive proposal covariance during warmup targeting ~25% acceptance
    rate.
  - Parameter transformations (log, logit) with Jacobian corrections for
    constrained parameters.
  - MCMC diagnostics: effective sample size (ESS), R-hat (split), MCSE,
    and acceptance rates.
  - Posterior impulse-response functions via irf() with pointwise
    credible bands computed from posterior draws.

                        Changes in version 0.2.0                        

Nonlinear DSGE support

  - New dsgenl_model() constructor for nonlinear DSGE models defined via
    string-based equations with VAR(+1) lead notation.
  - steady_state() generic for computing the deterministic steady state
    via Newton-Raphson with damped line search.
  - linearize() computes first-order Taylor expansion around steady
    state.
  - solve_dsge() and estimate() now accept dsgenl_model objects.

                        Changes in version 0.1.0                        

Initial release.

  - Formula-based linear model specification.
  - Klein (2000) solution via method of undetermined coefficients.
  - Maximum likelihood estimation via Kalman filter.
  - Policy/transition matrix extraction with delta-method standard
    errors.
  - Impulse-response functions, forecasting, stability diagnostics.