RtForecastR 0.1.1

• 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.

RtForecastR 0.1.0

• 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.