R: Ensemble Methods for Combining Hub Model Outputs

# Ensemble Methods for Combining Hub Model Outputs

## Documentation for package ‘hubEnsembles’ version 1.0.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

component_outputs | Example model output data for 'linear_pool()'
fweights | Example weights data for 'simple_ensemble()'
linear_pool | Compute ensemble model outputs as a linear pool, otherwise known as a distributional mixture, of component model outputs for each combination of model task, output type, and output type id. Supported output types include 'mean', 'quantile', 'cdf', 'pmf', and 'sample'.
make_sample_indices_unique | Make the output type ID values of sample forecasts distinct for different models
model_outputs | Example model output data for 'simple_ensemble()'
simple_ensemble | Compute ensemble model outputs by summarizing component model outputs for each combination of model task, output type, and output type id. Supported output types include 'mean', 'median', 'quantile', 'cdf', and 'pmf'.
validate_compound_taskid_set | Perform validations on the compound task ID set used to calculate an ensemble of component model outputs for the sample output type, including checks that (1) 'compound_taskid_set' is a subset of 'task_id_cols', (2) the provided 'model_out_tbl' is compatible with the specified 'compound_taskid_set', and (3) all models submit predictions for the same set of non 'compound_taskid_set' variables.
weights | Example weights data for 'linear_pool()'