Changes in version 0.1.1 (2026-08-21)                  

  - Bug fix: rt_forecast()'s forecast_quantiles element (used for
    weighted interval score calculations via wis()) was computed from a
    disconnected in-sample calculation that did not correspond to the
    genuine out-of-sample forecast reported in fit$forecast. It now
    derives directly from the same forecast distribution, so e.g.
    forecast_quantiles[["0.025"]] is guaranteed identical to
    c(fit$forecast$lo95, fit$forecast$hi95). Also fixes a duplicate
    "0.25" entry that could appear in forecast_quantiles when the
    default quantile_levels was used.

                 Changes in version 0.1.0 (2026-08-20)                  

  - Initial CRAN release.
  - rt_forecast(): filtered (real-time) and smoothed (retrospective) R_t
    estimation, one-step-ahead in-sample predictions, a genuine
    out-of-sample forecast, and elimination probability P(R_t < 1).
  - plot.rtforecast(): R_t, forecast, and observed-vs-predicted plots.
  - Forecast calibration metrics: mae(), mse(), rmse(), coverage(),
    interval_score(), wis().
  - score_batches(): score archived weekly forecast output against
    realized case counts.
  - Two bundled example datasets: measles_cdmx, jalisco.