| IGS | R Documentation | 
This score is suitable for tercile category forecasts. Using log2 for now (?).
IGS(
  dt,
  f = c("below", "normal", "above"),
  o = tc_cols(dt),
  by = by_cols_terc_fc_score(),
  pool = "year",
  dim.check = TRUE
)
dt | 
 Data table containing the predictions.  | 
f | 
 column names of the prediction.  | 
o | 
 column name of the observations (either in   | 
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.  | 
A data table with the scores
dt = data.table(below = c(0.5,0.3,0),
                normal = c(0.3,0.3,0.7),
                above = c(0.2,0.4,0.3),
                tc_cat = c(-1,0,0),
                lon = 1:3)
print(dt)
IGS(dt)
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