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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.
Health stats visible at Monitor.