Do Pairwise Comparison for one Set of Forecasts

This function does the pairwise comparison for one set of forecasts, but multiple models involved. It gets called from pairwise_comparison(). pairwise_comparison() splits the data into arbitrary subgroups specified by the user (e.g. if pairwise comparison should be done separately for different forecast targets) and then the actual pairwise comparison for that subgroup is managed from pairwise_comparison_one_group(). In order to actually do the comparison between two models over a subset of common forecasts it calls compare_two_models().

Usage

pairwise_comparison_one_group(scores, metric, baseline, by, ...)

Arguments

scores

A data.table of scores as produced by score().

metric

A character vector of length one with the metric to do the comparison on. The default is "auto", meaning that either "interval_score", "crps", or "brier_score" will be selected where available. See available_metrics() for available metrics.

baseline

character vector of length one that denotes the baseline model against which to compare other models.

by

character vector with names of columns present in the input data.frame. by determines how pairwise comparisons will be computed. You will get a relative skill score for every grouping level determined in by. If, for example, by = c("model", "location"). Then you will get a separate relative skill score for every model in every location. Internally, the data.frame will be split according by (but removing "model" before splitting) and the pairwise comparisons will be computed separately for the split data.frames.

...

additional arguments for the comparison between two models. See compare_two_models() for more information.