plot_calibration: Plot calibration curves
In dshemetov/evalcast-mirror: Tools For Evaluating COVID Forecasters

Plot calibration curves

plot_calibration(
  predictions_cards,
  type = c("wedgeplot", "traditional"),
  facet_rows = NULL,
  facet_cols = NULL,
  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
)

`predictions_cards`	Either one predictions_card or several joined together using bind_rows().
`type`	One of "wedgeplot" or "traditional"
`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 calibration. These determines the color of the lines and faceting depending on `type`
`avg_vars`	variables over which we average to determine the calibration.
`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?.