Table B.4 contains data on the annual U.S. production of blue and gorgonzola cheeses.
a. Fit an ARIMA model to this time series, excluding the last 10 observations. Investigate model adequacy. Explain how this model would be used for forecasting.
b. Forecast the last l 0 observations.
c. In Exercise 4.16, you were asked to use exponential smoothing methods to smooth the data, and to forecast the last 10 observations. Compare the ARIMA and exponential smoothing forecasts. Which forecasting method do you prefer?
d. How would prediction intervals be obtained for the ARIMA forecasts?
Exercise 4.16Table B.4 contains data on the annual U.S. production of blue and gorgonzola cheeses. This data has a strong trend.
TABLE B.4U.S. Production of Blue and Gorgonzola Cheeses
Year
Production (103lb)
Production ( 103lb)
1950
7,657
1974
28,262
1951
5,451
1975
28,506
1952
10,883
1976
33,885
1953
9,554
1977
34.776
1954
9,519
1978
35,347
1955
10,047
1979
34.628
1956
10,663
1980
33,043
1957
10,864
1981
30.214
1958
11,447
1982
31.013
1959
12,710
1983
31.496
1960
15,169
1984
34.115
1961
16,205
1985
33.433
1962
14,507
1986
34,198
1963
15,400
1987
35,863
1964
16,800
1988
37,789
1965
19,000
1989
34,561
1966
20,198
1990
36,434
1967
18,573
1991
34,371
1968
19,375
1992
33.307
1969
21,032
1993
33,295
1970
23,250
1994
36,514
1971
25,219
1995
36.593
1972
28,549
1996
38.311
1973
29,759
1997
42,773
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