Rank histogram for an ensemble. — ens_rank

The rank histogram is computed as columns in a harp_list object. Typically the scores are aggregated over lead time, but other grouping variables can be chosen.

Usage

ens_rank_histogram(
  .fcst,
  parameter,
  groupings = "lead_time",
  jitter_fcst = NULL,
  show_progress = TRUE,
  ...
)

# S3 method for harp_ens_point_df
ens_rank_histogram(
  .fcst,
  parameter,
  groupings = "lead_time",
  jitter_fcst = NULL,
  show_progress = TRUE,
  fcst_model = NULL,
  ...
)

Arguments

.fcst: A harp_df or harp_list object with tables that have a column for observations, or a single forecast table.
parameter: The name of the column for the observations data. Can be the column name, quoted, or unquoted. If a variable it should be embraced - i.e. wrapped in {{}}.
groupings: The groups for which to compute the scores. See group_by for more information of how grouping works.
jitter_fcst: A function to perturb the forecast values by. This is used to account for observation error in the rank histogram. For other statistics it is likely to make little difference since it is expected that the observations will have a mean error of zero.
show_progress: Logical - whether to show progress bars. Defaults to TRUE.
...: Reserved for methods.
fcst_model: The name of the forecast model to use in the fcst_model column of the output. If the function is dispatched on a harp_list object, the names of the harp_list are automatically used.

Value

An object of the same format as the inputs but with data grouped for the groupings column(s) and columns for rank and rank_count that are nested together in a column with the name rank_histogram.