Combine (Ensemble) Casts

Combine multiple forecasts' output into a single ensemble. Presently, only a general average ensemble is available.

Usage

ensemble_forecasts(
  main = ".",
  method = "unwtavg",
  forecasts_groups = NULL,
  forecasts_ids = NULL,
  forecast_table = NULL,
  historic_end_newmoonnumber = NULL,
  models = NULL,
  dataset = NULL,
  species = NULL
)

Arguments

main

character value of the name of the main component of the directory tree.

method

character value of the name of the ensemble method to use. Presently, only "unwtavg" (unweighted average) is allowed.

forecasts_groups

integer (or integer numeric) value of the forecasts groups to combine with an ensemble. If NULL (default), the most recent forecast group is ensembled.

forecasts_ids

integer (or integer numeric) values representing the forecasts of interest for restricting ensembling, as indexed within the directory in the casts sub folder. See the forecasts metadata file (forecasts_metadata.csv) for summary information.

forecast_table

Optional data.frame of forecast table outputs. If not input, will be loaded.

historic_end_newmoonnumber

integer (or integer numeric) newmoon number of the forecast origin. Default value is NULL, which equates to no selection.

models

character value(s) of the name of the model to include. Default value is NULL, which equates to no selection with respect to model. NULL translates to all models in the table.

dataset

character value of the rodent data set to include Default value is NULL, which equates to the first data set encountered.

species

character vector of the species code(s) or "total" for the total across species) to be plotted NULL translates to the species defined by forecasting_species called by prefab_species.

Value

data.frame of ensembled forecasts.

Details

A pre-loaded table of forecasts can be input, but if not (default), the table will be efficiently (as defined by the inputs) loaded and trimmed.
The forecasts can be trimmed specifically using the forecasts_ids input, otherwise, all relevant forecasts from the stated forecast_groups will be included.

See also

Core forecasting functions: evaluate forecasts, portalcast(), process forecast output

Examples

if (FALSE) { # \dontrun{
   main1 <- file.path(tempdir(), "ensemble")
   setup_production(main = main1)

   forecasts_ids <- select_forecasts(main     = main1, 
                                     datasets = "controls", 
                                     species  = "DM")$forecast_id

   ensemble_forecasts(main          = main1, 
                      forecasts_ids = forecasts_ids)

   unlink(main1, recursive = TRUE)
} # }