Forecast across multiple dates

Forecast across multiple dates

Usage

forecast_across_dates(
  obs,
  forecast_dates = unique(obs[!is.na(seq_available)])$date[-c(1:3)],
  ...
)

Arguments

obs

A data.frame with the following variables: date, cases, seq_voc, and seq_total, cases_available, and seq_available. seq_available and case_available must be uniquely define data rows but other rows can be duplicated based on data availability. This data format allows for multiple versions of case and sequence data for a given date with different reporting dates. This is important when using the package in evaluation settings or in real-time where data sources are liable to be updated as new data becomes available. See germany_covid19_delta_obs for an example of a supported data set.

forecast_dates

A list of dates to forecast at.

...

Additional parameters passed to forecast().

Value

A data.table each row containing the output from running forecast() on a single forecast date.

See also

Functions used for forecasting across models, dates, and scenarios forecast_across_scenarios(), forecast_n_strain(), forecast(), plot.fv_forecast(), summary.fv_forecast(), unnest_posterior()

Examples

if (FALSE) { # interactive()
library(ggplot2)
options(mc.cores = 4)

forecasts <- forecast_across_dates(
  germany_covid19_delta_obs,
  forecast_dates = c(as.Date("2021-05-01"), as.Date("2021-06-12")),
  horizon = 4,
  strains = 2,
  adapt_delta = 0.99,
  max_treedepth = 15,
  variant_relationship = "scaled"
)

# inspect forecasts
forecasts

# unnest posteriors
posteriors <- unnest_posterior(forecasts)

# plot case posterior predictions
plot_cases(posteriors, log = TRUE) +
  facet_grid(vars(forecast_date), vars(voc_scale))
}