This score is suitable for tercile category forecasts. This score is the frequency at which the highest probability category actually
happens. The function also provides the frequency at which the second-highest probability category, and lowest probability category,
actually happens.
Usage
HS(
dt,
f = c("below", "normal", "above"),
o = tc_cols(dt),
by = by_cols_terc_fc_score(),
pool = "year",
dim.check = TRUE
)
Value
A data table with the scores
Arguments
dt
Data table containing the predictions.
f
column names of the prediction.
o
column name of the observations (either in obs_dt, or in dt if obs_dt = NULL). The observation column needs to
contain -1 if it falls into the first category (corresponding to fcs[1]), 0 for the second and 1 for the third category.
by
column names of grouping variables, all of which need to be columns in dt.
Default is to group by all instances of month, season, lon, lat, system and lead_time that are columns in dt.
pool
column name(s) for the variable(s) along which is averaged, typically just 'year'.
dim.check
Logical. If TRUE, the function tests whether the data table contains only one row per coordinate-level, as should be the case.