EBMApredict | R Documentation |
Function allows users to create new predictions given an already estimated EBMA model This function produces predictions based on EBMA model weights and component model predictions.
EBMApredict(EBMAmodel, Predictions, Outcome = NULL, ...)
## S4 method for signature 'ForecastData'
EBMApredict(EBMAmodel, Predictions, Outcome = NULL, ...)
EBMAmodel |
An estimated EBMA model object |
Predictions |
A matrix with a column for each component model's predictions. |
Outcome |
An optional vector containing the true values of the dependent variable for all observations in the test period. |
... |
Not implemented |
Returns a data of class 'FDatFitLogit' or FDatFitNormal, a subclass of 'ForecastData', with the following slots:
predTest |
A matrix containing the predictions of all component models and the EBMA model for all observations in the test period. |
period |
The period, "calibration" or "test", for which the statistics were calculated. |
outcomeTest |
An optional vector containing the true values of the dependent variable for all observations in the test period. |
modelNames |
A character vector containing the names of all component models. If no model names are specified, names will be assigned automatically. |
modelWeights |
A vector containing the model weights assigned to each model. |
Michael D. Ward <michael.d.ward@duke.edu> and Jacob M. Montgomery <jacob.montgomery@wustl.edu> and Florian M. Hollenbach <florian.hollenbach@tamu.edu>
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. 31(3): 930-942.
Montgomery, Jacob M., Florian M. Hollenbach and Michael D. Ward. (2012). Improving Predictions Using Ensemble Bayesian Model Averaging. Political Analysis. 20: 271-291.
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