Plot interval width

plot_width(
  predictions_cards,
  facet_rows = "forecast_date",
  facet_cols = "forecaster",
  grp_vars = c("forecaster", "forecast_date", "ahead"),
  avg_vars = c("geo_value"),
  levels = c(0.5, 0.7, 0.9)
)

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. Alternatively, any data frame with columns `quantile`, `value` and any grouping vars and averaging vars.
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. Should be passed to plot_calibration when customized.
facet_cols	Same as `facet_rows`, but with columns.
grp_vars	variables over which to compare widths The first determines the color of the lines while the rest will be faceted over
avg_vars	variables over which we compute quantiles.
levels	Quantile levels for the summary of interval width, to be plotted. For example, `levels = c(0.5, 0.7, 0.9)`, the default, plots the median, 70% and 90% quantiles of interval widths.

Details

Interval width does not depend on the actual outcome, so this function can be called on predictions cards in addition to score cards.