setPredCalibration<- {EBMAforecast}

"Set" functions

Description

To assign individual slots, use set functions

Usage

setPredCalibration(object) <- value

## S4 replacement method for signature 'ForecastData'
setPredCalibration(object) <- value

setPredTest(object) <- value

## S4 replacement method for signature 'ForecastData'
setPredTest(object) <- value

setOutcomeCalibration(object) <- value

## S4 replacement method for signature 'ForecastData'
setOutcomeCalibration(object) <- value

setOutcomeTest(object) <- value

## S4 replacement method for signature 'ForecastData'
setOutcomeTest(object) <- value

setModelNames(object) <- value

## S4 replacement method for signature 'ForecastData'
setModelNames(object) <- value

Arguments

object

The object to which values are assigned.

value

Values to be assigned.

Value

A data object of the class 'ForecastData' with the following slots:

predCalibration

An array containing the predictions of all component models for all observations in the calibration period.

predTest

An array containing the predictions of all component models for all observations in the test period.

outcomeCalibration

A vector containing the true values of the dependent variable for all observations in the calibration period.

outcomeTest

A 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.

Author(s)

Michael D. Ward <[e-mail]> and Jacob M. Montgomery <[e-mail]> and Florian M. Hollenbach <[e-mail]>

References

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

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. 31:930–942.#'

Examples

## Not run: 
data(calibrationSample)
data(testSample)
setPredCalibration(this.ForecastData)<-calibrationSample[,c("LMER", "SAE", "GLM")]
setOutcomeCalibration(this.ForecastData)<-calibrationSample[,"Insurgency"]
setPredTest(this.ForecastData)<-testSample[,c("LMER", "SAE", "GLM")]
setOutcomeTest(this.ForecastData)<-testSample[,"Insurgency"]
setModelNames(this.ForecastData)<-c("LMER", "SAE", "GLM")

## End(Not run)