Australian Wine Sales. Figure 18 .32 shows time plots of monthly sales of six types of Australian wines (red, rose, sweet white, dry white, sparkling, and fortified) for 1980–1994. [Data are available in AustralianWines.csv, Source: Hyndman and Yang (2018).] The units are thousands of liters. You are hired to obtain short-term forecasts (two to three months ahead) for each of the six series, and this task will be repeated every month.

a. Comment on the suitability of a regression-based forecaster for each wine type.

b. Fortified wine has the largest market share of the above six types of wine. You are asked to focus on fortified wine sales alone and produce as accurate as possible forecasts for the next two months.

c. Create an ACF plot for the training residuals from the above model until lag-12. Examining this plot (only), which of the following statements are reasonable conclusions? • Decembers (month 12) are not captured well by the model. • There is a strong correlation between sales on the same calendar month. • The model does not capture the seasonality well. • We should try to fit an AR model with lag-12 to the residuals.

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Thousands of liters 600- 500- 400- 300- 200 Sweet wine 100- 1981 1983 1985 1987 1989 1991 1993 1995 Thousands of liters 250- 200 150 100- 50- Rose wine 1981 1983 1985 1987 1989 1991 1993 1995