tendency_diag: Tendency diagram from a data table containing tercile...

In SeasonalForecastingEngine/SeaVal: Validation of Seasonal Weather Forecasts

Tendency diagram from a data table containing tercile forecasts.

Description

Tendency diagram from a data table containing tercile forecasts.

Usage

tendency_diag(
  dt,
  f = c("below", "normal", "above"),
  o = tc_cols(dt),
  by = NULL,
  pool = setdiff(dimvars(dt), by),
  dim.check = TRUE
)

Arguments

dt	Data table containing tercile forecasts
f	column names of the prediction columns
o	column name of the observation column
by	column names of grouping variables. Default is to not group.
pool	column names of pooling variables (used for the dimension check). Default is all dimvars.
dim.check	Logical. If TRUE, the function checks whether the columns in by and pool span the entire data table.

Value

If by == NULL a gg object, otherwise a list of gg objects that can be plotted by ggpubr::ggarrange (for example)

Examples

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)
pp = tendency_diag(dt)
if(interactive()) plot(pp)

SeasonalForecastingEngine/SeaVal documentation built on June 23, 2024, 12:03 a.m.