Changes in version 0.1.2 (2026-07-16)                  

  - Documentation. Added an applied primer vignette ("A Primer on
    Location-Varying Gating for Quantile Mixtures") that walks
    social-science researchers through the concepts, data, fitting,
    interpretation, diagnostics, visualisation, and practical guidance
    with worked ggplot examples; and a formal PDF reference manual. Both
    are linked from the package website navbar.
  - Louis observed-information gate SEs. variance = "louis" computes the
    gate-block covariance by Louis's (1982) identity -- complete-data
    information minus the missing information from the latent labels --
    giving analytic, classification-aware standard errors without the
    imputation cost of "stochEM". In a Monte-Carlo check (n = 300) the
    Louis SE matched the empirical SD (0.207 vs 0.211) and reached 0.95
    coverage, where the conditional sandwich gave 0.80. This is the
    variance DESIGN section 2.4 specified; it is now the recommended
    choice for gate inference. summary() labels the SE method in use.

                        Changes in version 0.1.1                        

Revision after two adversarial reviews. The estimator was verified
correct; this release fixes the inference honesty and the software
contract.

  - Classification-aware gate SEs. mixqrgate(variance = "stochEM") adds
    a multiple-imputation gate variance that propagates the uncertainty
    about class membership. The default sandwich SE is conditional on
    the fitted memberships and under-covers when components overlap;
    summary() now says so.
  - Honest location-varying demo. sim_gate2() gains loc_vary, which
    makes membership genuinely depend on the quantile rank. The vignette
    is rewritten around inference (does the gate vary, with uncertainty
    shown) rather than an eyeballed trend; the previous example
    overstated a noisy drift.
  - Missing data. Component and gate designs are now built on the same
    complete-case rows, so y, X, and Z stay aligned.
  - confint() returns gate-coefficient intervals (previously empty);
    AIC(k=) honors k.
  - Guards: warnings on collapsed components, ill-conditioned gates, and
    non-convergence.
  - CRAN hygiene: .Rbuildignore, Remotes: for the non-CRAN mixqr
    dependency.

Still deferred (documented): full Louis joint gate+component
information, a cross-tau Wald test, KDE-path classification-aware gate
SEs, cross-tau relabel coherence, and vary_gating = "smooth".

                        Changes in version 0.1.0                        

First release. A companion to mixqr adding a concomitant,
quantile-indexed mixing gate to finite mixtures of quantile regressions.

  - mixqrgate() fits a gated mixture: the mixing probabilities follow a
    multinomial-logit gate on concomitant covariates (gating = ~ z),
    optionally refit per quantile level (vary_gating = "discrete", the
    Furno 2025 location-varying mixing mode). ALD and Wu & Yao
    kernel-density paths.
  - The gate M-step is a weighted multinomial-logistic regression solved
    by ridge-penalised Newton/IRLS, with sandwich standard errors -- the
    inference on how membership varies that Furno's heuristic lacks.
  - Reduces exactly to a constant gate (and the plain mixqr fit) when
    gating = ~1.
  - Reuses the mixqr component and constrained-error-density machinery
    via its extension API (weighted_rq(), constrained_kde()).
  - S3 methods: print, summary (component + gate blocks), coef, vcov,
    predict, plot(which = "gating") (the gate-vs-tau picture), logLik,
    AIC, BIC, fitted, residuals.
  - sim_gate2() simulates a two-component design with a concomitant
    gate.