EBMAforecast

Description

The EBMAforecast package (currently under development) allows users to increase the accuracy of forecasting models by pooling multiple component forecasts to generate ensemble forecasts. It includes functions to fit an ensemble Bayesian model averaging (EBMA) model using in-sample predictions, generate ensemble out-of-sample predictions, and create useful data visualizations. Currently, the package can only handle dichotomous outcomes or those with normally distributed errors, although additional models will be added to the package in the coming months. Missing observation are allowed in the calibration set, but models with many predictions missing are penalized.

Author(s)

Michael D. Ward <michael.d.ward@duke.edu> and Jacob M. Montgomery <jacob.montgomery@wustl.edu> and Florian M. Hollenbach <florian.hollenbach@tamu.edu>

References

Montgomery, Jacob M., Florian M. Hollenbach and Michael D. Ward. (2015). Calibrating ensemble forecasting models with sparse data in the social sciences. International Journal of Forecasting. In Press.

Montgomery, Jacob M., Florian M. Hollenbach and Michael D. Ward. (2012). Improving Predictions Using Ensemble Bayesian Model Averaging. Political Analysis. 20: 271-291.

Raftery, A. E., T. Gneiting, F. Balabdaoui and M. Polakowski. (2005). Using Bayesian Model Averaging to calibrate forecast ensembles. Monthly Weather Review. 133:1155–1174.

Sloughter, J. M., A. E. Raftery, T. Gneiting and C. Fraley. (2007). Probabilistic quantitative precipitation forecasting using Bayesian model averaging. Monthly Weather Review. 135:3209–3220.

Fraley, C., A. E. Raftery, T. Gneiting. (2010). Calibrating Multi-Model Forecast Ensembles with Exchangeable and Missing Members using Bayesian Model Averaging. Monthly Weather Review. 138:190–202.

Sloughter, J. M., T. Gneiting and A. E. Raftery. (2010). Probabilistic wind speed forecasting using ensembles and Bayesian model averaging. Journal of the American Statistical Association. 105:25–35.

Fraley, C., A. E. Raftery, and T. Gneiting. (2010). Calibrating multimodel forecast ensembles with exchangeable and missing members using Bayesian model averaging. Monthly Weather Review. 138:190–202.

Examples

## Not run: demo(EBMAforecast)
demo(presForecast)

## End(Not run)

Results