g do not show the validation data. create a plot to show the forecast and prediction interval. fit an arima model (20 points) looking at the training data: what level of differencing do you need? create an acf and pacf plot on the differenced data. what ar and ma terms do you need? what arima model would you recommend for this data? (if you are unsure then try several) fit your recommended arima model. create a plot to compare the fit to the training data. do not show the validation data. create a plot to show the forecast and prediction interval. use auto.arima() to fit an arima (p, d, q) (p, d, q) model to the training data (10 points) create a plot to compare the fit to the training data. do not show the validation data. create a plot to show the forecast and prediction interval. fit an exponential smoothing model (20 points) looking at the training data: is there a trend? what form does it take? is there seasonality? what form does it take? what ets() model would you recommend for this data? (if you are unsure then try several) fit your recommended ets model. create a plot to compare the fit to the training data. do not show the validation data. create a plot to show the forecast and prediction interval. fit an ets model allowing the algorithm to choose the structure for error, trend and seasonality from the training data (10 points) create a plot to compare the fit to the training data. do not show the validation data. create a plot to show the forecast and prediction interval. assess the predictive accuracy of your five models in cross-validation (10 points) which model would you recommend to the australian tourism board for forecasting trips to the victoria region (20 points) create a plot to compare the fit of your recommended model to the training and validation data. create a plot to show a 3-year forecast and prediction interval for your chosen model based on the full dataset.