Interpretation of the check_test_point() function


I tried to build a linear regression (y_obs ~ Bernoulli). The inference run, however, I do not know how to interpret the model.check_test_point().

Could you please guide me on where I can read more about?

I will include below the output that I got.

alpha -0.92
beta0 -0.92
beta1 -0.92
y_obs -22.18
Name: Log-probability of test_point, dtype: float64

Many thanks

Check test point is usually for checking whether the default value of your model makes sense. Usually if any number is NaN your model would immediately have problem.
The value beside each variable is the log probability, conditioned on the default value (i.e., model.test_point)