profit_graph: (Accumulative) profit graphs

In SeaVal: Validation of Seasonal Weather Forecasts

(Accumulative) profit graphs

Description

These graphs really only make sense if you have 50 or less observations. Typical application would be when you compare seasonal mean forecasts to station data for a single location.

Usage

profit_graph(
  dt,
  accumulative = TRUE,
  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
accumulative	Logic. Should the accumulative profit be plotted or the profit per forecast?
f	column names of the prediction columns
o	column name of the observation column
by	column names of grouping variables. Default is NULL.
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

A list of gg objects which 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)
p1 = profit_graph(dt)
p2 = profit_graph(dt,accumulative = FALSE)

if(interactive()){
plot(p1)
plot(p2)
}

SeaVal documentation built on June 24, 2024, 5:15 p.m.