Decide on and build plot methods

[dashaub]

Any ideas for plotting our ensemble object? Want to include ggplot2 in addition to base graphics? For the individual component models we can use the individual plot methods from the "forecast" package for each model. For example, plot(hybridModel(wineind, models = "aten")) could be setup to create a 2x2 plot by par(mfrow = c(2, 2)) and then plot the Arima/tbats/ets/nnetar objects using the forecast package's methods. The nnetar object does not have a plot method, so that will need to be excluded, and the plot.Arima() method already sets par(mfrow = c(1, 2)), so this approach might need some work. If we want to plot both the individual component models and something for the ensemble we could put in a "Hit to see the next plot:" prompt like in the plot.lm() method

[dashaub]

Basic--fairly horrific--plotting is implemented here: 657c5b83a967f59ee0668ffaffbe3e9f6bb01f84 It merely plots the original series and the fitted values. The idea of plotting each of the models by setting mfrow won't work because some of the individual models themselves change this in their own plot methods. Upon reflection, the "Hit to see the next plot:" behavior of plot.lm() is an anomaly and shouldn't be emulated. We could just splatter all of the individual model plots one after another.

[dashaub]

This second behavior is implemented here with type = "models": 241e002e28b08070eda16533cb5d5af774650f26 We can add ggplot support and other plot types later, especially once the forecast package itself implemented ggplot.