Plot interval coverage

plot_coverage(
  predictions_cards,
  type = c("all", "one"),
  coverage = 0.8,
  facet_rows = c("forecaster"),
  facet_cols = c("forecast_date"),
  grp_vars = c("forecaster", "forecast_date", "ahead"),
  avg_vars = c("geo_value"),
  geo_type = c("county", "hrr", "msa", "dma", "state", "hhs", "nation"),
  backfill_buffer = 0
)

Arguments

predictions_cards	tibble of predictions that are all for the same prediction task, meaning they are for the same response, incidence period,and geo type. Forecasts may be for a different forecast date or forecaster. A predictions card may be created by the function `get_predictions()`, downloaded with `get_covidhub_predictions()` or possibly created manually.
type	One of "all" or "one", indicating whether to show coverage across all nominal levels (in which case averaging is performed across `avg_vars`) or whether to show it for one specific alpha value.
coverage	If `type = "one"`, then coverage is the nominal interval coverage shown.
facet_rows	A variable name to facet data over. Creates a separate row of plots for each value of specified variable. Can be used with `facet_cols` to create a grid of plots.
facet_cols	Same as `facet_rows`, but with columns.
grp_vars	variables over which to compare coverage
avg_vars	variables over which we average to determine the proportion of coverage.
geo_type	String indicating geographical type, such as "county", or "state". See the COVIDcast Geographic Coding documentation for available options.
backfill_buffer	How many days until response is deemed trustworthy enough to be taken as correct?