some new features
This commit is contained in:
ilgazca
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apply,pared,public,gpa
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very likely,0,0,3.26
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somewhat likely,1,0,3.21
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unlikely,1,1,3.94
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somewhat likely,0,0,2.81
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somewhat likely,0,0,2.53
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||||
unlikely,0,1,2.59
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||||
somewhat likely,0,0,2.56
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||||
somewhat likely,0,0,2.73
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||||
unlikely,0,0,3.0
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||||
somewhat likely,1,0,3.5
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||||
unlikely,1,1,3.65
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||||
somewhat likely,0,0,2.84
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very likely,0,1,3.9
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somewhat likely,0,0,2.68
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||||
unlikely,1,0,3.57
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||||
unlikely,0,0,3.09
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||||
unlikely,0,1,3.5
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||||
unlikely,0,0,2.17
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||||
very likely,0,1,3.36
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||||
somewhat likely,0,0,3.4
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||||
very likely,0,0,2.75
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||||
somewhat likely,1,0,3.2
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||||
unlikely,0,0,2.44
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||||
unlikely,0,0,2.83
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||||
unlikely,0,1,3.0
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||||
somewhat likely,0,1,3.27
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somewhat likely,1,0,3.14
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||||
somewhat likely,0,0,3.37
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very likely,0,1,2.79
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unlikely,0,0,2.9
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somewhat likely,0,0,3.38
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unlikely,0,1,2.95
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unlikely,0,0,2.98
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unlikely,1,1,3.81
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unlikely,0,0,2.74
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unlikely,0,0,2.62
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||||
unlikely,0,0,2.85
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||||
somewhat likely,0,0,2.5
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somewhat likely,0,0,2.75
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unlikely,0,0,2.26
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||||
unlikely,0,0,2.03
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somewhat likely,1,0,2.85
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unlikely,0,0,2.72
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somewhat likely,0,0,2.89
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somewhat likely,1,0,2.47
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unlikely,0,0,3.04
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unlikely,0,0,3.1
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unlikely,0,0,2.57
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unlikely,0,0,2.09
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somewhat likely,0,0,2.94
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unlikely,0,0,3.45
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unlikely,0,0,2.76
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very likely,0,1,2.96
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unlikely,0,0,2.89
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somewhat likely,0,0,2.97
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somewhat likely,0,1,3.91
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somewhat likely,0,0,2.77
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unlikely,0,0,2.51
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unlikely,0,0,3.24
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unlikely,0,0,2.44
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somewhat likely,0,0,2.78
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unlikely,0,0,2.94
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unlikely,1,0,3.22
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||||
unlikely,0,0,3.5
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very likely,1,0,3.57
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somewhat likely,0,0,3.17
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unlikely,0,1,3.23
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unlikely,0,0,2.91
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unlikely,0,0,3.28
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unlikely,0,1,3.32
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unlikely,0,0,3.62
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unlikely,0,0,2.55
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unlikely,0,0,2.97
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very likely,1,0,3.63
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unlikely,0,1,3.02
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unlikely,0,1,3.6
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unlikely,0,0,2.95
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very likely,1,1,3.81
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somewhat likely,1,0,2.68
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unlikely,1,0,3.72
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unlikely,0,0,2.49
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unlikely,0,0,2.72
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unlikely,1,0,2.25
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unlikely,0,0,2.53
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unlikely,0,0,3.26
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very likely,0,0,2.57
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unlikely,0,0,2.9
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unlikely,0,0,3.05
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somewhat likely,0,0,2.85
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somewhat likely,0,0,4.0
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very likely,1,0,3.4
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somewhat likely,0,1,3.24
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unlikely,0,1,3.51
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very likely,0,0,2.55
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unlikely,0,0,3.06
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very likely,0,0,3.0
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somewhat likely,0,0,3.13
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unlikely,0,0,3.16
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somewhat likely,0,0,2.47
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somewhat likely,0,0,2.89
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unlikely,0,0,2.74
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unlikely,0,0,3.16
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unlikely,0,0,2.92
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somewhat likely,0,0,3.57
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somewhat likely,1,0,3.49
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somewhat likely,0,1,2.56
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somewhat likely,1,0,3.12
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somewhat likely,1,0,2.65
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somewhat likely,0,0,2.51
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somewhat likely,0,0,3.08
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somewhat likely,0,0,2.65
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unlikely,0,0,2.99
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unlikely,0,0,2.63
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somewhat likely,0,0,2.8
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somewhat likely,0,1,3.46
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unlikely,0,0,3.61
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unlikely,0,0,3.08
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unlikely,1,0,3.28
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unlikely,0,1,3.31
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unlikely,0,0,2.57
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somewhat likely,0,0,3.39
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unlikely,0,0,2.26
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unlikely,0,0,2.42
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unlikely,0,0,2.6
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somewhat likely,1,1,3.44
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somewhat likely,0,0,2.98
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somewhat likely,1,0,3.09
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unlikely,0,1,3.34
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unlikely,0,0,2.84
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unlikely,0,0,2.81
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unlikely,0,0,2.79
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unlikely,0,0,2.4
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unlikely,0,0,3.02
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somewhat likely,0,0,2.65
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somewhat likely,0,0,2.55
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somewhat likely,1,0,3.12
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unlikely,0,0,2.98
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very likely,1,0,3.61
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unlikely,0,0,2.98
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unlikely,0,0,3.19
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unlikely,0,0,3.51
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unlikely,0,0,3.1
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unlikely,0,0,3.55
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unlikely,0,0,2.98
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very likely,0,0,2.99
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unlikely,0,0,3.05
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unlikely,0,0,2.99
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unlikely,0,0,2.32
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unlikely,0,0,2.5
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unlikely,0,1,2.9
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very likely,1,1,3.28
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somewhat likely,0,0,2.95
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somewhat likely,0,0,3.54
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somewhat likely,0,0,3.11
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unlikely,1,0,3.25
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unlikely,0,0,2.44
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unlikely,0,0,2.13
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somewhat likely,0,0,3.22
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somewhat likely,0,0,3.16
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unlikely,0,0,3.39
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somewhat likely,0,0,2.7
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somewhat likely,0,0,3.09
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somewhat likely,0,0,3.16
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unlikely,0,0,2.28
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unlikely,0,0,2.91
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unlikely,0,0,3.65
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unlikely,0,0,2.86
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unlikely,0,1,3.39
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unlikely,0,0,3.71
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unlikely,0,0,3.25
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unlikely,0,0,3.14
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unlikely,0,0,2.41
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somewhat likely,0,0,3.08
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unlikely,0,1,3.02
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somewhat likely,0,0,3.15
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very likely,0,0,2.95
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unlikely,0,0,2.22
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somewhat likely,0,0,2.86
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somewhat likely,1,0,2.88
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very likely,0,0,2.62
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unlikely,0,0,3.37
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somewhat likely,0,0,3.51
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somewhat likely,0,0,3.65
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very likely,1,0,3.42
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very likely,0,0,2.41
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very likely,0,1,3.21
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unlikely,0,0,3.22
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unlikely,0,0,2.53
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somewhat likely,0,0,2.64
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unlikely,0,0,2.94
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somewhat likely,0,0,2.56
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unlikely,0,1,3.12
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somewhat likely,0,0,3.34
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unlikely,0,0,3.22
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somewhat likely,0,0,3.05
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somewhat likely,0,0,3.29
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somewhat likely,0,0,2.71
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unlikely,0,0,2.87
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unlikely,0,0,3.29
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unlikely,0,0,3.36
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unlikely,1,1,2.85
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unlikely,0,0,2.79
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somewhat likely,0,0,3.69
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very likely,0,0,3.56
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unlikely,0,0,3.52
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unlikely,1,1,3.38
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very likely,0,1,3.11
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somewhat likely,1,0,3.2
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unlikely,0,0,2.83
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unlikely,0,0,3.08
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very likely,0,1,2.97
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unlikely,0,0,2.64
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unlikely,0,0,2.47
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very likely,0,0,3.07
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somewhat likely,0,0,3.2
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unlikely,0,0,2.55
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unlikely,0,0,2.48
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unlikely,0,0,3.29
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somewhat likely,0,0,2.64
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somewhat likely,0,0,3.22
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somewhat likely,1,0,2.8
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somewhat likely,0,0,3.62
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unlikely,0,0,2.62
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somewhat likely,0,1,3.04
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unlikely,0,1,2.49
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unlikely,0,1,3.1
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very likely,1,0,3.15
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somewhat likely,0,0,2.65
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unlikely,0,0,3.04
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unlikely,0,1,3.05
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unlikely,0,0,2.88
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somewhat likely,0,0,2.86
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somewhat likely,0,0,3.0
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unlikely,0,0,2.23
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unlikely,0,1,3.14
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unlikely,0,0,2.67
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unlikely,0,0,3.11
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somewhat likely,0,0,3.73
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somewhat likely,0,0,2.45
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unlikely,0,0,3.04
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unlikely,0,0,2.4
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somewhat likely,0,0,3.43
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somewhat likely,0,0,2.57
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unlikely,0,0,2.84
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unlikely,0,0,2.67
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very likely,1,1,3.45
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somewhat likely,1,0,2.88
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somewhat likely,0,0,2.78
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unlikely,0,0,3.22
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unlikely,1,0,3.3
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somewhat likely,1,0,2.86
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somewhat likely,0,0,2.83
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somewhat likely,0,0,3.7
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somewhat likely,0,0,3.15
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somewhat likely,1,1,3.08
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unlikely,0,0,2.92
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unlikely,0,0,2.89
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very likely,1,0,3.53
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unlikely,0,0,3.1
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somewhat likely,1,0,3.36
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somewhat likely,0,0,2.74
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somewhat likely,0,0,2.73
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unlikely,1,0,2.72
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unlikely,0,0,3.53
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unlikely,1,0,3.45
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unlikely,0,0,2.98
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somewhat likely,0,0,2.88
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very likely,1,0,3.21
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unlikely,0,0,3.06
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unlikely,0,0,2.4
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somewhat likely,0,0,3.57
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unlikely,1,0,2.88
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unlikely,0,0,3.27
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unlikely,0,0,2.92
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very likely,0,0,2.7
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somewhat likely,1,0,2.53
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somewhat likely,0,0,3.38
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unlikely,0,0,3.16
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somewhat likely,0,0,2.6
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unlikely,0,0,2.76
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unlikely,0,0,3.56
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unlikely,0,0,2.87
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somewhat likely,1,0,2.99
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unlikely,0,0,2.68
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unlikely,0,0,2.99
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somewhat likely,0,0,2.96
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unlikely,1,1,2.77
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somewhat likely,0,0,3.28
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unlikely,0,1,2.74
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unlikely,0,0,1.9
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unlikely,0,0,3.05
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somewhat likely,0,1,2.44
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somewhat likely,0,0,3.33
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somewhat likely,0,1,3.56
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unlikely,0,0,2.15
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unlikely,0,0,2.83
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somewhat likely,0,0,2.79
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somewhat likely,0,0,2.72
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very likely,1,0,3.04
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unlikely,0,1,3.03
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unlikely,0,0,2.88
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somewhat likely,0,0,3.21
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unlikely,0,0,2.74
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unlikely,0,0,3.57
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somewhat likely,0,0,2.43
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unlikely,0,0,3.11
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unlikely,0,0,2.76
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somewhat likely,0,0,3.13
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unlikely,0,0,2.75
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unlikely,0,0,2.6
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unlikely,0,0,3.67
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unlikely,0,0,3.26
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unlikely,0,0,3.41
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very likely,0,0,3.24
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||||
unlikely,0,0,3.05
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somewhat likely,1,0,2.38
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||||
somewhat likely,0,0,2.61
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somewhat likely,1,1,3.18
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unlikely,0,0,3.34
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somewhat likely,0,0,2.84
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unlikely,0,0,2.8
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unlikely,0,0,3.21
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unlikely,0,0,2.63
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unlikely,0,0,2.31
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unlikely,0,0,2.29
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unlikely,0,0,3.51
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somewhat likely,0,0,2.87
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unlikely,0,0,3.09
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||||
somewhat likely,1,0,2.88
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||||
unlikely,1,0,2.47
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||||
somewhat likely,0,1,3.72
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||||
unlikely,0,0,3.2
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somewhat likely,0,0,2.57
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unlikely,0,0,3.05
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||||
unlikely,0,0,3.27
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||||
unlikely,0,0,3.3
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unlikely,0,0,2.73
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||||
unlikely,1,0,2.63
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||||
unlikely,0,0,2.77
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||||
unlikely,0,0,3.15
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||||
unlikely,0,0,2.85
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||||
unlikely,0,0,2.25
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||||
somewhat likely,0,0,3.56
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||||
unlikely,0,0,2.7
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||||
very likely,0,0,2.94
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||||
somewhat likely,1,0,2.58
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||||
somewhat likely,0,0,2.97
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||||
very likely,0,0,3.38
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||||
very likely,0,0,2.96
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||||
unlikely,0,0,2.44
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||||
somewhat likely,0,1,3.75
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||||
somewhat likely,0,0,3.07
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||||
somewhat likely,0,0,2.72
|
||||
unlikely,0,0,3.13
|
||||
unlikely,0,0,3.39
|
||||
unlikely,0,1,2.38
|
||||
somewhat likely,0,0,2.87
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||||
unlikely,0,1,2.91
|
||||
very likely,1,0,3.25
|
||||
somewhat likely,1,1,3.51
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||||
unlikely,1,0,3.65
|
||||
somewhat likely,0,0,3.11
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||||
very likely,0,0,2.71
|
||||
unlikely,0,0,3.05
|
||||
unlikely,0,0,2.93
|
||||
somewhat likely,0,0,2.35
|
||||
somewhat likely,0,0,2.49
|
||||
unlikely,0,0,3.26
|
||||
unlikely,0,0,3.77
|
||||
unlikely,0,1,3.49
|
||||
unlikely,0,0,3.39
|
||||
unlikely,0,0,3.37
|
||||
unlikely,0,0,1.98
|
||||
unlikely,1,0,2.93
|
||||
unlikely,0,0,3.36
|
||||
unlikely,0,0,3.12
|
||||
somewhat likely,0,0,3.23
|
||||
somewhat likely,0,1,3.9
|
||||
unlikely,0,0,2.7
|
||||
unlikely,0,0,2.34
|
||||
unlikely,0,0,3.3
|
||||
somewhat likely,0,0,3.11
|
||||
unlikely,0,0,3.14
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||||
somewhat likely,1,0,3.68
|
||||
somewhat likely,0,0,2.22
|
||||
unlikely,0,0,2.61
|
||||
somewhat likely,0,1,3.48
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||||
very likely,0,0,3.08
|
||||
unlikely,0,0,2.79
|
||||
unlikely,0,0,3.12
|
||||
unlikely,0,1,2.67
|
||||
somewhat likely,0,0,3.54
|
||||
very likely,0,0,2.98
|
||||
somewhat likely,1,0,3.32
|
||||
somewhat likely,1,0,3.54
|
||||
unlikely,0,0,3.7
|
||||
unlikely,0,0,2.63
|
||||
somewhat likely,0,0,2.25
|
||||
somewhat likely,0,0,3.26
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||||
very likely,0,0,3.52
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||||
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@ -0,0 +1,122 @@
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"""
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Test Results for ordinal models from R MASS lib
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"""
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||||
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||||
import numpy as np
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import os
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import pandas as pd
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||||
from statsmodels.tools.testing import Holder
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# R (v3.4.4) code inspired from
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# https://stats.idre.ucla.edu/r/dae/ordinal-logistic-regression/
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||||
# library(readr) # to open the file
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||||
# library(MASS) # to perform ordinal regression
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||||
#
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||||
# ## load the data, 400 rows with 3 exogs(2 binaries, 1 float)
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||||
# ##and target 3-ordinal variable
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||||
# ologit_ucla <- read_csv("ologit_ucla.csv")
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||||
# ologit_ucla$apply <- as.factor(ologit_ucla$apply)
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||||
# ologit_ucla$apply <- factor(ologit_ucla$apply,
|
||||
# levels=c("unlikely", "somewhat likely", "very likely"))
|
||||
#
|
||||
# ## fit ordered logit model
|
||||
# r_logit <- polr(apply ~ pared + public + gpa,
|
||||
# data = ologit_ucla,
|
||||
# method = 'logit', # or 'probit'
|
||||
# Hess=TRUE)
|
||||
#
|
||||
# ## fit ordered probit model
|
||||
# r_probit <- polr(apply ~ pared + public + gpa,
|
||||
# data = ologit_ucla,
|
||||
# method = 'probit',
|
||||
# Hess=TRUE)
|
||||
#
|
||||
# ## fit ordered cloglog model
|
||||
# r_cloglog <- polr(apply ~ pared + public + gpa,
|
||||
# data = ologit_ucla,
|
||||
# method = 'cloglog',
|
||||
# Hess=TRUE)
|
||||
#
|
||||
# ## with r = r_logit or r_probit or r_cloglog
|
||||
# ## we add p-values
|
||||
# (ctable <- coef(summary(r)))
|
||||
# p <- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE) * 2
|
||||
# (ctable <- cbind(ctable, "p value" = p))
|
||||
# ## show 7 first predictions
|
||||
# head(predict(r, subset(ologit_ucla,
|
||||
# select=c("pared", "public","gpa")), type='prob'),7)
|
||||
|
||||
data_store = Holder()
|
||||
cur_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
df = pd.read_csv(os.path.join(cur_dir, "ologit_ucla.csv"))
|
||||
|
||||
# df_unordered['apply'] is pd.Categorical with ordered = False
|
||||
df_unordered = df.copy()
|
||||
df_unordered['apply'] = pd.Categorical(df['apply'], ordered=False)
|
||||
# but categories are set in order
|
||||
df_unordered['apply'] = df_unordered['apply'].cat.set_categories(
|
||||
['unlikely', 'somewhat likely', 'very likely'])
|
||||
|
||||
# df['apply'] is pd.Categorical with ordered = True
|
||||
df['apply'] = pd.Categorical(df['apply'], ordered=True)
|
||||
df['apply'] = df['apply'].cat.set_categories(
|
||||
['unlikely', 'somewhat likely', 'very likely'])
|
||||
|
||||
data_store.df_unordered = df_unordered
|
||||
data_store.df = df
|
||||
data_store.nobs = 400
|
||||
data_store.n_ordinal_cat = 3
|
||||
|
||||
res_ord_logit = Holder()
|
||||
res_ord_logit.coefficients_val = \
|
||||
np.array([1.04769011, -0.05878572, 0.61594057])
|
||||
res_ord_logit.coefficients_stdE = np.array([0.2658, 0.2979, 0.2606])
|
||||
res_ord_logit.coefficients_tval = np.array([3.9418, -0.1974, 2.3632])
|
||||
res_ord_logit.coefficients_pval = \
|
||||
np.array([8.087070e-05, 8.435464e-01, 1.811594e-02])
|
||||
res_ord_logit.thresholds = np.array([2.203915, 4.299363])
|
||||
res_ord_logit.prob_pred = np.array([[0.5488310, 0.3593310, 0.09183798],
|
||||
[0.3055632, 0.4759496, 0.21848725],
|
||||
[0.2293835, 0.4781951, 0.29242138],
|
||||
[0.6161224, 0.3126888, 0.07118879],
|
||||
[0.6560149, 0.2833901, 0.06059505],
|
||||
[0.6609240, 0.2797117, 0.05936431],
|
||||
[0.6518332, 0.2865114, 0.06165547]])
|
||||
res_ord_logit.resid_prob = np.array(
|
||||
[+0.90816202, 0.08707593, -0.77061649, 0.54493358, 0.59541984,
|
||||
-0.33907603, 0.59017771, 0.55970937, -0.41190566, 0.01851403,
|
||||
-0.73753054, 0.53932241, 0.87609730, 0.56880356, -0.73936739,
|
||||
-0.42539653, -0.47329831, -0.29581150, 0.90792753, 0.42811409])
|
||||
res_ord_logit.resid_prob_stats = [
|
||||
3.5137670974297e-06, -0.7706164931682951, 0.9434781714439548,
|
||||
0.2550630116905416]
|
||||
|
||||
res_ord_probit = Holder()
|
||||
res_ord_probit.coefficients_val = np.array([0.59811, 0.01016, 0.35815])
|
||||
res_ord_probit.coefficients_stdE = np.array([0.1579, 0.1728, 0.1568])
|
||||
res_ord_probit.coefficients_tval = np.array([3.78881, 0.05878, 2.28479])
|
||||
res_ord_probit.coefficients_pval = \
|
||||
np.array([1.513681e-04, 9.531256e-01, 2.232519e-02])
|
||||
res_ord_probit.thresholds = np.array([1.2968, 2.5028])
|
||||
res_ord_probit.prob_pred = np.array([[0.5514181, 0.3576848, 0.09089707],
|
||||
[0.3260107, 0.4488799, 0.22510933],
|
||||
[0.2349733, 0.4506351, 0.31439162],
|
||||
[0.6142501, 0.3184778, 0.06727214],
|
||||
[0.6519891, 0.2928449, 0.05516602],
|
||||
[0.6402204, 0.3009945, 0.05878509],
|
||||
[0.6480094, 0.2956162, 0.05637442]])
|
||||
|
||||
res_ord_cloglog = Holder()
|
||||
res_ord_cloglog.coefficients_val = np.array([0.5166455, 0.1081131, 0.3343895])
|
||||
res_ord_cloglog.coefficients_stdE = np.array([0.1613525, 0.1680675, 0.1542065])
|
||||
res_ord_cloglog.coefficients_tval = np.array([3.2019668, 0.6432721, 2.1684534])
|
||||
res_ord_cloglog.coefficients_pval = \
|
||||
np.array([1.364927e-03, 5.200475e-01, 3.012421e-02])
|
||||
res_ord_cloglog.thresholds = np.array([0.8705304, 1.9744660])
|
||||
res_ord_cloglog.prob_pred = np.array([[0.5519526, 0.3592524, 0.08879500],
|
||||
[0.3855287, 0.3842645, 0.23020682],
|
||||
[0.2899487, 0.3540202, 0.35603111],
|
||||
[0.6067184, 0.3333548, 0.05992678],
|
||||
[0.6411418, 0.3133969, 0.04546127],
|
||||
[0.5940557, 0.3400072, 0.06593710],
|
||||
[0.6374521, 0.3156622, 0.04688570]])
|
||||
Reference in New Issue
Block a user