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13 0 1 2011 1 0.5 0.67 0.67 0 0.5 11 8 7 18 12 20 12
8 1 1 2011 0.89 0.5 0.83 0.33 0.5 1 19 18 20 23 20 19 8
14 0 1 2011 0.89 0.4 1 0.67 0 1 16 12 9 22 14 18 11
16 1 1 2011 0.89 0.5 0.83 0 0 0 24 24 19 22 25 24 13
14 1 1 2011 0.89 0.7 0.67 0 1 1 15 16 12 19 15 20 11
13 1 1 2011 0.78 0.3 0 0 0.5 0.5 17 19 16 25 20 20 10
15 0 1 2011 0.89 0.4 0.83 0.67 0.5 0 19 16 17 28 21 24 7
13 1 1 2011 1 0.4 0.5 0.67 1 1 19 15 9 16 15 21 10
20 1 1 2011 0.89 0.7 0.83 0 0.5 0 28 28 28 28 28 28 15
17 1 1 2011 0.78 0.6 0.33 0.67 0.5 0.5 26 21 20 21 11 10 12
15 1 1 2011 1 0.6 0.5 1 0 0.5 15 18 16 22 22 22 12
16 1 1 2011 0.78 0.2 0.67 0 0.5 0.5 26 22 22 24 22 19 10
12 1 1 2011 0.89 0.4 1 0 0.5 0.5 16 19 17 24 27 27 10
17 0 1 2011 0.89 0.4 0.5 0.67 0 1 24 22 12 26 24 23 14
11 0 1 2011 0.89 0.5 0.67 0.33 0 0 25 25 18 28 23 24 6
16 0 0 2011 0.89 0.3 0.17 0.67 0 0.5 22 20 20 24 24 24 12
16 1 1 2011 0.89 0.4 0.83 0.33 0.5 0.5 15 16 12 20 21 25 14
15 0 1 2011 0.67 0.7 0.67 0.33 0.5 1 21 19 16 26 20 24 11
13 1 0 2011 1 0.5 0.67 0.33 0 1 22 18 16 21 19 21 8
14 0 1 2011 0.78 0.2 0.67 0 0 1 27 26 21 28 25 28 12
19 1 1 2011 0.78 0.3 0.5 0.67 0 0.5 26 24 15 27 16 28 15
16 1 1 2011 0.89 0.6 1 0.33 0 1 26 20 17 23 24 22 13
17 0 1 2011 0.78 0.6 0.83 0.33 0 1 22 19 17 24 21 26 11
10 1 1 2011 0.89 0.2 0.83 0.33 0 1 21 19 17 24 22 26 12
15 1 1 2011 0.89 0.7 1 0.67 1 0 22 23 18 22 25 21 7
14 1 1 2011 0.33 0.2 0.67 0 0 0 20 18 15 21 23 26 11
14 1 0 2011 1 1 1 0.33 1 1 21 16 20 25 20 23 7
16 0 0 2011 0.89 0.4 0.83 0.67 0 0.5 20 18 13 20 21 20 12
15 1 1 2011 0.89 0.4 1 1 0 1 22 21 21 21 22 24 12
17 0 1 2011 0.67 0.2 0.83 0.67 0 0.5 21 20 12 26 25 25 13
14 0 1 2011 0.56 0.4 0.67 0.33 0 1 8 15 6 23 23 24 9
16 0 1 2011 0.89 0.4 0.67 0 0.5 1 22 19 13 21 19 20 11
15 1 1 2011 0.89 0.7 1 0.67 0.5 0.5 20 19 19 27 21 24 12
16 1 1 2011 1 0.2 0.67 0.67 0 0.5 24 7 12 25 19 25 15
16 1 1 2011 0.78 0.6 1 1 0 0.5 17 20 14 23 25 23 12
10 1 1 2011 0.78 0.3 1 1 0.5 0.5 20 20 13 25 16 21 6
8 0 1 2011 0.33 0.3 0.5 0.33 0 0 23 19 12 23 24 23 5
17 1 0 2011 0.78 0.2 0.67 0 0.5 0 20 19 17 19 24 21 13
14 1 1 2011 0.89 0.5 0.83 0.67 0.5 0.5 22 20 19 22 18 18 11
10 0 1 2011 0.89 0.7 1 0.67 0.5 1 19 18 10 24 28 24 6
14 1 1 2011 0.78 0.6 1 0.67 0.5 0.5 15 14 10 19 15 18 12
12 1 1 2011 0.89 0.4 1 0.67 0.5 1 20 17 11 21 17 21 10
16 1 1 2011 0.89 0.6 1 0.33 0.5 1 22 17 11 27 18 23 6
16 1 1 2011 1 0.4 1 1 0 1 17 8 10 25 26 25 12
16 1 0 2011 0.67 0.3 0.83 0.67 0 1 14 9 7 25 18 22 11
8 0 1 2011 1 0.5 0.83 0.67 0.5 0.5 24 22 22 23 22 22 6
16 1 1 2011 0.89 0.2 0.5 0 0 1 17 20 12 17 19 23 12
15 1 0 2011 0.89 0.3 0.83 0 0.5 1 23 20 18 28 17 24 12
8 0 1 2011 0.89 0.5 0.17 0 0 1 25 22 20 25 26 25 8
13 1 0 2011 0.78 0.7 0.83 1 0.5 1 16 22 9 20 21 22 10
14 1 0 2011 0.89 0.4 1 0.67 1 0.5 18 22 16 25 26 24 11
13 1 0 2011 0.78 0.3 1 0 0 0.5 20 16 14 21 21 21 7
16 1 1 2011 0.78 0.2 0.67 0.67 1 1 18 14 11 24 12 24 12
19 1 0 2011 1 0.5 1 0 0 0.5 23 24 20 28 20 25 13
19 1 1 2011 0.78 0.4 1 0 0.5 0 24 21 17 20 20 23 14
14 1 1 2011 1 0.6 1 0.67 1 1 23 20 14 19 24 27 12
15 0 0 2011 0.78 0.4 0.83 1 0 1 13 20 8 24 24 27 6
13 1 1 2011 0.67 0.4 0.33 0 0 0.5 20 18 16 21 22 23 14
10 0 0 2011 0.33 0.2 0.33 0.33 0 0 20 14 11 24 21 18 10
16 1 0 2011 1 0.9 1 0.67 0.5 1 19 19 10 23 20 20 12
15 1 1 2011 1 0.8 1 0.67 1 0.5 22 24 15 18 23 23 11
11 0 1 2011 0.78 0.8 0.83 0 0.5 1 22 19 15 27 19 24 10
9 0 1 2011 0.67 0.3 1 1 0.5 1 15 16 10 25 24 26 7
16 1 1 2011 1 0.2 0.83 0.67 0 0.5 17 16 10 20 21 20 12
12 0 1 2011 0.89 0.4 0.67 0 0.5 1 19 16 18 21 16 23 7
12 1 0 2011 0.89 0.2 0.83 1 0 1 20 14 10 23 17 22 12
14 0 1 2011 0.78 0.2 0.67 0.67 0.5 1 22 22 22 27 23 23 12
14 1 1 2011 1 0.1 0.83 0.67 0 1 21 21 16 24 20 17 10
13 1 1 2011 0.56 0.4 0.67 1 0.5 0 21 15 10 27 19 20 10
15 0 0 2011 0.67 0.5 1 0 0.5 0.5 16 14 7 24 18 22 12
17 0 1 2011 0.89 0.8 0.83 0.33 0.5 1 20 15 16 23 18 18 12
14 0 1 2011 0.89 0.4 0.67 0.67 0 0.5 21 14 16 24 21 19 12
11 0 0 2011 0.89 0.6 0.83 0.33 0.5 0.5 20 20 16 21 20 19 8
9 1 0 2011 0.89 0.5 0.83 0.67 0.5 1 23 21 22 23 17 16 10
7 0 1 2011 0.78 0.3 0.67 0 0 0 18 14 5 27 25 26 5
15 0 1 2011 1 0.4 0.33 0 0.5 0 16 16 10 25 17 25 10
12 1 0 2011 1 0.6 0.83 0.67 0.5 0.5 17 13 8 19 17 23 12
15 0 1 2011 0.89 0.4 1 0.33 0 0.5 24 26 16 24 24 18 11
14 0 0 2011 0.44 0.3 0.83 0 0 0 13 13 8 25 21 22 9
16 1 1 2011 0.78 0.8 0.83 0 1 1 19 18 16 23 22 26 12
14 0 0 2011 0.89 0.6 0.5 0.33 1 1 20 15 14 23 18 25 11
13 0 0 2011 0.67 0.3 0.5 0 0 0 22 18 15 25 22 26 10
16 0 0 2011 0.78 0.5 0.83 0.67 0.5 1 19 21 9 26 20 26 12
13 1 0 2011 0.78 0.4 1 0.33 0 1 21 17 21 26 21 24 10
16 0 0 2011 0.33 0.3 0.33 0.67 0 0 15 18 7 16 21 22 9
16 1 0 2011 0.89 0.7 1 0.33 0 0.5 21 20 17 23 20 21 11
16 1 0 2011 0.89 0.2 0.67 0.33 0.5 0.5 24 18 18 26 18 22 12
10 0 0 2011 0.89 0.4 0.83 1 0 1 22 25 16 25 25 28 7
12 0 0 2011 0.89 0.6 1 0.67 0.5 0.5 20 20 16 23 23 22 11
12 0 0 2011 0.56 0.6 0.83 0 0 1 21 19 14 26 21 26 12
12 1 0 2011 0.67 0.6 0.83 0.67 0.5 0.5 19 18 15 22 20 20 6
12 1 0 2011 0.67 0.4 1 0.33 0.5 1 14 12 8 20 21 24 9
19 1 0 2011 0.78 0.6 0.83 0 0 1 25 22 22 27 20 21 15
14 0 0 2011 0.78 0.5 1 0.33 0.5 1 11 16 5 20 22 23 10
13 1 0 2011 0.78 0.5 0.83 0 0 1 17 18 13 22 15 23 11
16 0 0 2011 0.89 0.6 0.67 0 0 1 22 23 22 24 24 23 12
15 1 0 2011 1 0.8 0.83 0.33 0.5 1 20 20 18 21 22 22 12
12 1 0 2011 0.89 0.5 0.83 0.67 1 0.5 22 20 15 24 21 23 12
8 1 0 2011 0.89 0.6 0.83 0.67 0.5 1 15 16 11 26 17 21 11
10 1 0 2011 0.78 0.4 0.83 0.67 0.5 1 23 22 19 24 23 27 9
16 1 0 2011 1 0.3 0.67 0.67 0.5 1 20 19 19 24 22 23 11
16 0 0 2011 0.78 0.3 0.83 1 0 0.5 22 23 21 27 23 26 12
10 1 0 2011 0.67 0.2 0 0 0 0 16 6 4 25 16 27 12
18 1 0 2011 0.78 0.4 0.83 0 0 0.5 25 19 17 27 18 27 14
12 1 0 2011 0.89 0.5 1 0 0 0.5 18 24 10 19 25 23 8
16 0 0 2011 0.67 0.3 0.17 0 0.5 0 19 19 13 22 18 23 10
10 0 0 2011 0.22 0.4 0.17 0 0.5 0 25 15 15 22 14 23 9
14 0 0 2011 0.44 0.5 0.5 1 0 0 21 18 11 25 20 28 10
12 0 0 2011 0.89 0.3 0.5 0.67 0 1 22 18 20 23 19 24 9
11 0 0 2011 0.67 0.5 1 0 0 0.5 21 22 13 24 18 20 10
15 0 0 2011 0.89 0.4 0.67 0.67 0 0.5 22 23 18 24 22 23 12
7 1 0 2011 0.67 0.4 0.83 0.67 0 1 23 18 20 23 21 22 11
16 1 1 2012 0.78 0.6 1 0 1 1 20 17 15 22 14 15 9
16 1 1 2012 0.78 0.3 1 0.67 1 1 6 6 4 24 5 27 11
16 1 1 2012 0.78 0.4 1 0.33 1 0.5 15 22 9 19 25 23 12
16 1 1 2012 1 0.3 1 1 1 1 18 20 18 25 21 23 12
12 0 0 2012 0.78 1 1 1 1 1 24 16 12 26 11 20 7
15 1 0 2012 0.67 0.4 1 0 0 0.5 22 16 17 18 20 18 12
14 1 1 2012 0.89 0.8 0.83 1 0.5 1 21 17 12 24 9 22 12
15 0 1 2012 0.89 0.3 1 0.67 1 1 23 20 16 28 15 20 12
16 1 1 2012 1 0.5 0.83 0.67 0 1 20 23 17 23 23 21 10
13 0 1 2012 0.78 0.4 1 0 0 0.5 20 18 14 19 21 25 15
10 0 1 2012 0.67 0.3 0.83 0.67 0 1 18 13 13 19 9 19 10
17 1 1 2012 0.89 0.5 0.83 1 0 1 25 22 20 27 24 25 15
15 1 1 2012 0.67 0.3 1 0.67 0 1 16 20 16 24 16 24 10
18 1 1 2012 0.67 0.3 0.67 0 0 1 20 20 15 26 20 22 15
16 1 1 2012 1 0.4 0.83 0 0 1 14 13 10 21 15 28 9
20 1 1 2012 0.67 0.3 1 0 0 0.5 22 16 16 25 18 22 15
16 1 0 2012 1 0.6 1 0.33 0.5 0.5 26 25 21 28 22 21 12
17 1 1 2012 0.89 0.6 0.83 0.67 1 1 20 16 15 19 21 23 13
16 1 1 2012 0.89 0.4 1 1 1 1 17 15 16 20 21 19 12
15 0 1 2012 1 0.4 1 0 0 0 22 19 19 26 21 21 12
13 1 1 2012 0.67 0.4 1 0.67 0 0.5 22 19 9 27 20 25 8
16 1 1 2012 0.44 0.3 0.67 0.67 0.5 1 20 24 19 23 24 23 9
16 1 1 2012 0.89 0.2 1 0.33 1 0 17 9 7 18 15 28 15
16 1 1 2012 0.56 0.5 0.83 0.67 0 1 22 22 23 23 24 14 12
17 1 1 2012 0.78 0.4 1 0.67 1 1 17 15 14 21 18 23 12
20 1 1 2012 1 0.4 1 0.67 0 0 22 22 10 23 24 24 15
14 0 1 2012 1 0.4 0.83 0.67 0 1 21 22 16 22 24 25 11
17 1 1 2012 0.89 0.3 0.67 0.67 0.5 0.5 25 24 12 21 15 15 12
6 1 0 2012 0.67 0.4 0.83 0.67 1 0.5 11 12 10 14 19 23 6
16 1 1 2012 0.89 0.2 1 0.33 0.5 1 19 21 7 24 20 26 14
15 1 1 2012 0.33 0 0 0 0 0 24 25 20 26 26 21 12
16 1 1 2012 0.89 0.4 1 0.67 0.5 1 17 26 9 24 26 26 12
16 0 1 2012 0.78 0.6 1 0 1 1 22 21 12 22 23 23 12
14 0 1 2012 1 0.4 0.67 0.67 0 0.5 17 14 10 20 13 15 11
16 1 1 2012 0.44 0.4 1 0 0 0.5 26 28 19 20 16 16 12
16 0 1 2012 0.67 0.4 0.83 0 0.5 0 20 21 11 18 22 20 12
16 0 1 2012 0.33 0.2 0.17 0 0.5 0 19 16 15 18 21 20 12
14 1 1 2012 0.89 0.4 0.83 1 1 1 21 16 14 25 11 21 12
14 0 1 2012 0.89 0.3 0.83 0 0 0.5 24 25 11 28 23 28 8
16 1 1 2012 1 0.6 0.83 0.67 1 0 21 21 14 23 18 19 8
16 1 1 2012 0.89 0.6 0.83 1 0 1 19 22 15 20 19 21 12
15 0 1 2012 0.89 0.4 0.83 0 0 1 13 9 7 22 15 22 12
16 1 0 2012 1 0.5 1 0.67 1 0.5 24 20 22 27 8 27 11
16 1 0 2012 0.89 0.4 0.83 0 0.5 1 28 19 19 24 15 20 10
18 1 1 2012 1 0.6 1 1 1 1 27 24 22 23 21 17 11
15 0 1 2012 0.78 0.6 0.83 0.67 0.5 1 22 22 11 20 25 26 12
16 0 0 2012 0.78 0.9 1 0.67 0.5 1 23 22 19 22 14 21 13
16 0 0 2012 0.67 0.4 0.83 0.67 0.5 0 19 12 9 21 21 24 12
16 0 0 2012 0.89 0.8 1 1 0.5 1 18 17 11 24 18 21 12
17 1 0 2012 0.67 0.5 0.83 1 0 1 23 18 17 26 18 25 10
14 0 1 2012 0.78 0.4 0.83 1 0 0 21 10 12 24 12 22 10
18 1 1 2012 0.89 0.4 1 0.67 1 0.5 22 22 17 18 24 17 11
9 0 0 2012 0.89 0.7 1 1 1 0.5 17 24 10 17 17 14 8
15 1 0 2012 0.78 0.4 1 0.33 1 1 15 18 17 23 20 23 12
14 0 0 2012 1 0.8 1 0.67 0.5 1 21 18 13 21 24 28 9
15 1 0 2012 1 0.4 1 1 1 0.5 20 23 11 21 22 24 12
13 0 0 2012 1 0.3 1 0.67 0 0.5 26 21 19 24 15 22 9
16 0 0 2012 0.67 0.5 1 0.67 0.5 1 19 21 21 22 22 24 11
20 1 0 2012 0.89 0.8 1 0.67 1 1 28 28 24 24 26 25 15
14 0 0 2012 1 0.4 0.83 0.33 0 0.5 21 17 13 24 17 21 8
12 1 0 2012 1 1 1 1 0.5 0 19 21 16 24 23 22 8
15 1 1 2012 0.89 0.5 1 0.67 1 1 22 21 13 23 19 16 11
15 1 1 2012 0.89 0.5 1 0.67 1 1 21 20 15 21 21 18 11
15 1 0 2012 0.89 0.3 1 0.33 0 1 20 18 15 24 23 27 11
16 1 1 2012 0.89 0.3 0.83 0.33 0.5 1 19 17 11 19 19 17 13
11 0 1 2012 0.89 0.3 0.5 0 0 1 11 7 7 19 18 25 7
16 1 0 2012 1 0.4 0.67 0.33 0.5 0.5 17 17 13 23 16 24 12
7 0 1 2012 0.67 0.5 1 0.33 0 1 19 14 13 25 23 21 8
11 0 0 2012 1 0.5 0.67 0.67 0.5 1 20 18 12 24 13 21 8
9 0 0 2012 0.89 0.4 1 0 0 0 17 14 8 21 18 19 4
15 1 1 2012 0.89 0.7 1 1 0.5 0 21 23 7 18 23 27 11
16 0 0 2012 0.89 0.5 0.5 0.33 0 0.5 21 20 17 23 21 28 10
14 1 0 2012 0.89 0.4 0.67 0.33 1 0 12 14 9 20 23 19 7
15 0 0 2012 1 0.7 0.67 1 0 1 23 17 18 23 16 23 12
13 0 0 2012 1 0.7 0.67 1 0 1 22 21 17 23 17 25 11
13 0 0 2012 1 0.7 0.67 1 0 1 22 23 17 23 20 26 9
12 0 0 2012 0.89 0.7 0.67 1 0 1 21 24 18 23 18 25 10
16 1 0 2012 0.89 0.7 0.67 0 0 0 20 21 12 27 20 25 8
14 1 0 2012 0.89 0.7 1 0.67 0.5 1 18 14 14 19 19 24 8
16 1 0 2012 0.33 0.1 0.67 0.33 0.5 0 21 24 22 25 26 24 11
14 1 0 2012 0.67 0.2 0.67 0.67 0.5 1 24 16 19 25 9 24 12
15 0 0 2012 0.56 0.3 0.33 0.33 0 1 22 21 21 21 23 22 10
10 0 0 2012 0.44 0.6 0.83 0.33 0 0.5 20 8 10 25 9 21 10
16 1 0 2012 1 0.8 1 1 1 1 17 17 16 17 13 17 12
14 0 1 2012 0.89 0.8 1 0.33 0.5 0.5 19 18 11 22 27 23 8
16 0 0 2012 0.33 0 0.17 0 0 0 16 17 15 23 22 17 11
12 0 0 2012 0.67 0.3 0.67 0.33 0 1 19 16 12 27 12 25 8
16 0 0 2012 0.67 0.6 0.83 0.33 0.5 1 23 22 21 27 18 19 10
16 1 1 2012 1 0.5 0.83 0.67 0 1 8 17 22 5 6 8 14
15 1 0 2012 0.78 0.7 1 0.33 0 0.5 22 21 20 19 17 14 9
14 0 1 2012 0.67 0.3 0.83 0 0.5 1 23 20 15 24 22 22 9
16 0 0 2012 1 0.3 1 0.67 0 0 15 20 9 23 22 25 10
11 1 1 2012 0.78 0.4 1 0.67 0 0.5 17 19 15 28 23 28 13
15 0 0 2012 0.89 0.4 0.83 1 0 1 21 8 14 25 19 25 12
18 1 1 2012 0.89 0.1 0.83 0 0 1 25 19 11 27 20 24 13
13 1 0 2012 0.89 0.5 1 0.67 0 1 18 11 9 16 17 15 8
7 0 0 2012 0 0 0 0 0 0 20 13 12 25 24 24 3
7 1 0 2012 0.67 0.4 1 0.33 0.5 0 21 18 11 26 20 28 8
17 1 0 2012 1 0.6 0.83 0.67 1 0.5 21 19 14 24 18 24 12
18 1 1 2012 1 0.4 1 0.33 0.5 1 24 23 10 23 23 25 11
15 0 1 2012 0.67 0.1 0.33 0 0.5 1 22 20 18 24 27 23 9
8 0 0 2012 0.89 0.3 0.83 0 0 1 22 22 11 27 25 26 12
13 0 1 2012 0.89 0.7 0.83 0.67 0 1 23 19 14 25 24 26 12
13 1 1 2012 0.56 0.3 0.17 0 0 1 17 16 16 19 12 22 12
15 1 0 2012 0.67 0.5 0.83 0.33 0.5 0 15 11 11 19 16 25 10
18 1 1 2012 1 0.3 0.83 0.67 1 1 22 21 16 24 24 22 13
16 1 0 2012 1 0.6 0.67 0.67 0.5 1 19 14 13 20 23 26 9
14 0 0 2012 1 0.9 1 1 0 1 18 21 12 21 24 20 12
15 0 1 2012 0.67 0.4 0.83 0 0.5 1 21 20 17 28 24 26 11
19 0 0 2012 0.44 0.3 1 0 0.5 0.5 20 21 23 26 26 26 14
16 1 1 2012 0.89 0.9 1 0.67 1 1 19 20 14 19 19 21 11
12 1 1 2012 0.44 0.5 1 0 0.5 0 19 19 10 23 28 21 9
16 0 1 2012 0.56 0.3 1 1 0.5 0.5 16 19 16 23 23 24 12
11 0 0 2012 0.89 0.6 0.83 0.67 0 0.5 18 18 11 21 21 21 8
16 0 1 2012 0.67 0.2 1 0.33 0 0.5 23 20 16 26 19 18 15
15 1 0 2012 0.89 0.4 0.83 1 0.5 1 22 21 19 25 23 23 12
19 1 1 2012 1 0.5 0.83 0.67 0.5 0.5 23 22 17 25 23 26 14
15 0 1 2012 0.78 0.4 0.83 0.67 0 0.5 20 19 12 24 20 23 12
14 0 1 2012 0.44 0 0 0 0 0 24 23 17 23 18 25 9
14 0 1 2012 0.89 0.2 1 0.33 0.5 1 25 16 11 22 20 20 9
17 1 0 2012 0.89 0.5 1 0.67 0.5 1 25 23 19 27 28 25 13
16 1 1 2012 0.89 0.3 1 0.67 0 0.5 20 18 12 26 21 26 13
20 1 1 2012 0.44 0 0 0 0 0 23 23 8 23 25 19 15
16 1 1 2012 1 0.5 0.83 1 0 1 21 20 17 22 18 21 11
9 0 0 2012 0.89 0.6 0.83 0.33 0 1 23 20 13 26 24 23 7
13 1 1 2012 0.67 0.3 0.83 0 0.5 0.5 23 23 17 22 28 24 10
15 1 1 2012 0.33 0 0 0 0 0 11 13 7 17 9 6 11
19 1 0 2012 0.78 0.3 0.67 0 0.5 0 21 21 23 25 22 22 14
16 0 1 2012 0.89 0.5 1 0.67 0.5 1 27 26 18 22 26 21 14
17 0 0 2012 0.78 0.4 0.67 0 0 1 19 18 13 28 28 28 13
16 1 0 2012 0.78 0.5 0.83 0.67 0 0.5 21 19 17 22 18 24 12
9 0 0 2012 0.89 0.7 1 1 1 0.5 16 18 13 21 23 14 8
11 1 0 2012 0.78 0.8 1 0.67 0.5 1 21 18 8 24 15 20 13
14 1 0 2012 0.78 0.6 1 0.33 0.5 1 22 19 16 26 24 28 9
19 0 1 2012 0.67 0.4 0.83 0.33 0 0.5 16 13 14 26 12 19 12
13 1 1 2012 0.89 0.5 0.83 0.33 0.5 0 18 10 13 24 12 24 13
14 0 1 2012 0.89 0.5 1 0 0.5 1 23 21 19 27 20 21 11
15 1 1 2012 0.78 0.3 1 0.33 0 1 24 24 15 22 25 21 11
15 1 1 2012 1 0.6 1 0 0.5 1 20 21 15 23 24 26 13
14 0 1 2012 1 0.3 0.67 0.67 0 0.5 20 23 8 22 23 24 12
16 1 0 2012 0.78 0.6 0.83 1 0.5 0.5 18 18 14 23 18 26 12
17 0 0 2012 0.78 0.3 0.33 0.33 0 1 4 11 7 15 20 25 10
12 1 1 2012 0.89 0.7 1 0.67 1 1 14 16 11 20 22 23 9
15 0 0 2012 0.89 0.7 1 1 0 1 22 20 17 22 20 24 10
17 1 0 2012 0.67 0.6 0.67 1 0.5 1 17 20 19 25 25 24 13
15 0 1 2012 1 0.5 1 0.33 0.5 0 23 26 17 27 28 26 13
10 0 0 2012 0.67 0.5 0.83 0.33 0 0.5 20 21 12 24 25 23 9
16 1 0 2012 0.56 0.4 0.67 0 0 1 18 12 12 21 14 20 11
15 1 0 2012 0.78 0.4 1 0.33 1 1 19 15 18 17 16 16 12
11 0 0 2012 1 0.7 1 1 0 1 20 18 16 26 24 24 8
16 1 0 2012 0.67 0.2 0.17 0 0.5 0 15 14 15 20 13 20 12
16 1 0 2012 0.78 0.5 0.83 0.67 0 0.5 24 18 20 22 19 23 12
16 0 0 2012 0.56 0.4 0.83 0.67 0.5 0 21 16 16 24 18 23 12
14 1 0 2012 1 0.2 1 0.67 1 1 19 19 12 23 16 18 9
14 0 0 2012 0.89 0.5 0.67 0.67 0 0 19 7 10 22 8 21 12
16 0 0 2012 0.44 0.4 0.5 0 0 1 27 21 28 28 27 25 12
16 1 0 2012 1 0.7 0.67 1 1 1 23 24 19 21 23 23 11
18 1 0 2012 0.89 0.6 0.83 0.67 1 0 23 21 18 24 20 26 12
14 0 0 2012 0.78 0.4 0.83 0 0 0 20 20 19 28 20 26 6
20 1 0 2012 0.89 0.5 1 0.67 1 1 17 22 8 25 26 24 7
15 0 0 2012 0.11 0 0.17 0 0 0 21 17 17 24 23 23 10
16 0 0 2012 0.89 0.7 1 0.67 0.5 1 23 19 16 24 24 21 12
16 1 0 2012 0.89 0.4 0.67 0.67 0 1 22 20 18 21 21 23 10
16 0 1 2012 1 0.5 0.67 1 0 1 16 16 12 20 15 20 12
12 0 0 2012 0.89 0.6 0.83 0.67 0 0.5 20 20 17 26 22 23 9
8 1 0 2012 1 0.8 0.5 0.67 0.5 0.5 16 16 13 16 25 24 3

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
mywarning <- ''
par1 <- as.numeric(par1)
if(is.na(par1)) {
par1 <- 1
mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.'
}
if (par4=='') par4 <- 0
par4 <- as.numeric(par4)
if (par5=='') par5 <- 0
par5 <- as.numeric(par5)
x <- na.omit(t(y))
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'Seasonal Differences (s=12)'){
(n <- n - 12)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+12,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'First and Seasonal Differences (s=12)'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
(n <- n - 12)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+12,j] - x[i,j]
}
}
x <- x2
}
if(par4 > 0) {
x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep='')))
for (i in 1:(n-par4)) {
for (j in 1:par4) {
x2[i,j] <- x[i+par4-j,par1]
}
}
x <- cbind(x[(par4+1):n,], x2)
n <- n - par4
}
if(par5 > 0) {
x2 <- array(0, dim=c(n-par5*12,par5), dimnames=list(1:(n-par5*12), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep='')))
for (i in 1:(n-par5*12)) {
for (j in 1:par5) {
x2[i,j] <- x[i+par5*12-j*12,par1]
}
}
x <- cbind(x[(par5*12+1):n,], x2)
n <- n - par5*12
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
(k <- length(x[n,]))
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
(k <- length(x[n,]))
head(x)
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, mywarning)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
if(n < 200) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' '))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}
}