The example has two input tables, input table glm_test1 and model table glm_output1.
In glm_test1, the column temp contains temperature readings and the column damage contains indicators of whether damage occurred at the corresponding temperature (1 for yes, 0 for no).
GLMPredict Example 3 Input Table glm_test1
temp |
damage |
63 |
1 |
67 |
0 |
67 |
0 |
67 |
0 |
75 |
0 |
75 |
1 |
79 |
0 |
58 |
1 |
66 |
0 |
70 |
1 |
70 |
0 |
70 |
1 |
70 |
0 |
78 |
0 |
53 |
5 |
57 |
1 |
69 |
0 |
73 |
0 |
81 |
0 |
68 |
0 |
72 |
0 |
76 |
0 |
76 |
0 |
GLMPredict Example 3 Model Table glm_output1 (Columns 1-5)
attribute |
predictor |
category |
estimate |
std_error |
1 |
temp |
|
-0.174664 |
0.0176891 |
0 |
(Intercept) |
|
10.5672 |
1.06526 |
-1 |
Loglik |
|
-49.7719 |
23 |
GLMPredict Example 3 Model Table glm_output1 (Columns 6-9)
z_score |
p_value |
significance |
family |
-9.87414 |
0 |
*** |
POISSON |
9.91976 |
0 |
*** |
POISSON |
1 |
0 |
|
POISSON |