A function to plot a holtWinters timeseries in ggplot2

HWplot.R

#HWplot.R

library(ggplot2)
library(reshape)


HWplot<-function(ts_object, n.ahead=4, CI=.95, error.ribbon='green', line.size=1){
  
  hw_object<-HoltWinters(ts_object)
  
  forecast<-predict(hw_object, n.ahead=n.ahead, prediction.interval=T, level=CI)
  
  
  for_values<-data.frame(time=round(time(forecast), 3), value_forecast=as.data.frame(forecast)$fit, dev=as.data.frame(forecast)$upr-as.data.frame(forecast)$fit)
  
  fitted_values<-data.frame(time=round(time(hw_object$fitted), 3), value_fitted=as.data.frame(hw_object$fitted)$xhat)
  
  actual_values<-data.frame(time=round(time(hw_object$x), 3), Actual=c(hw_object$x))
  
  
  graphset<-merge(actual_values, fitted_values, by='time', all=TRUE)
  graphset<-merge(graphset, for_values, all=TRUE, by='time')
  graphset[is.na(graphset$dev), ]$dev<-0
  
  graphset$Fitted<-c(rep(NA, NROW(graphset)-(NROW(for_values) + NROW(fitted_values))), fitted_values$value_fitted, for_values$value_forecast)
  
  
  graphset.melt<-melt(graphset[, c('time', 'Actual', 'Fitted')], id='time')
  
  p<-ggplot(graphset.melt, aes(x=time, y=value)) + geom_ribbon(data=graphset, aes(x=time, y=Fitted, ymin=Fitted-dev, ymax=Fitted + dev), alpha=.2, fill=error.ribbon) + geom_line(aes(colour=variable), size=line.size) + geom_vline(x=max(actual_values$time), lty=2) + xlab('Time') + ylab('Value') + opts(legend.position='bottom') + scale_colour_hue('')
  
  result.list <- list(plot = p, forecast = for_values, fitted = fitted_values, actual = actual_values, hwobject = hw_object)
  return(result.list)
  
}

Demo of use:

myHWplot <- HWplot(your_time_series)

# output plot
myHWplot$p

# forecasted values
myHWplot$forecast

#fitted values
myHWplot$fitted

#your original data
myHWplot$actual

#the HW object for use in other functions
myHWplot$hwobject

I googled for the source as I copied it from somewhere, this looks like original https://github.com/Crytics/Forecasting/blob/master/HW_Forecast