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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.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.mae(),
mse(), rmse(), coverage(),
interval_score(), wis().score_batches(): score archived weekly forecast output
against realized case counts.measles_cdmx,
jalisco.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.