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Data:
88 1 94 2 90 2 73 2 68 1 80 2 86 2 86 3 91 3 79 1 96 3 92 2 72 3 96 2 70 1 86 2 87 2 88 3 79 2 90 1 95 2 85 2 90 2 115 3 84 3 79 2 94 1 97 2 86 2 111 3 87 2 98 3 87 3 68 1 88 1 82 3 111 3 75 2 94 1 95 1 80 1 95 2 68 2 94 1 88 1 84 3 101 1 98 2 78 3 109 2 102 2 81 1 97 3 75 3 97 2 101 1 101 3 95 2 95 2 95 2 90 1 107 2 92 3 86 2 70 1 95 3 96 1 91 2 87 3 92 1 97 3 102 2 91 1 68 2 88 1 97 2 90 2 101 3 94 3 101 3 109 3 100 2 103 2 94 2 97 3 85 1 75 1 77 2 87 1 78 3 108 2 97 2 106 2 107 2 95 2 107 3 115 2 101 2 85 3 90 3 115 3 95 2 97 2 112 1 97 3 77 2 90 2 94 2 103 2 77 2 98 1 90 2 111 2 77 1 88 1 75 2 92 3 78 1 106 3 80 1 87 2 92 2 86 1 85 3 90 2 101 3 94 2 86 2 86 3 90 2 75 3 86 2 91 1 97 2 91 1 70 1 98 1 96 1 95 2 100 2 95 2 97 1 97 3 92 3 115 3 88 2 87 1 100 2 98 3 102 2 96 1
Sample Range:
(leave blank to include all observations)
From:
To:
Number of time lags
Default
5
6
7
8
9
10
11
12
24
36
48
60
Box-Cox transformation parameter (Lambda)
1
-2.0
-1.9
-1.8
-1.7
-1.6
-1.5
-1.4
-1.3
-1.2
-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
Degree of non-seasonal differencing (d)
0
1
2
Degree of seasonal differencing (D)
0
1
2
Seasonality
12
1
2
3
4
6
12
CI type
White Noise
MA
Confidence Interval
Use logarithms with this base
(overrules the Box-Cox lambda parameter)
(?)
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