rel_diag {SeaVal}

Reliability Diagrams for tercile forecasts

Description

Creates reliability diagrams from a data table containing tercile forecasts It wraps rel_diag_vec, see ?rel_diag_vec for more details. about the output diagrams. The output format is very much inspired by Figure 5 of Mason&2018. By default, 4 diagrams are drawn, one for each the prediction of above-, normal- and below-values, plus one for all forecasts together. You can provide a 'by' argument to obtain separate reliability diagrams for different values of the by-columns. E.g., when you data table contains a column named 'season', you can set by = 'season'. Then, the function will output a list of 16 diagrams, 4 for each season.

Usage

rel_diag(
  dt,
  f = c("below", "normal", "above"),
  o = tc_cols(dt),
  by = NULL,
  pool = setdiff(dimvars(dt), by),
  binwidth = 0.05,
  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.

binwidth

bin width for discretizing probabilities.

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