statsmodels.discrete.discrete_model.Probit.score_obs

Probit.score_obs(params) [source]

Probit model Jacobian for each observation

Parameters:	params (array-like) – The parameters of the model
Returns:	jac – The derivative of the loglikelihood for each observation evaluated at params.
Return type:	array-like

Notes

\[\frac{\partial\ln L_{i}}{\partial\beta}=\left[\frac{q_{i}\phi\left(q_{i}x_{i}^{\prime}\beta\right)}{\Phi\left(q_{i}x_{i}^{\prime}\beta\right)}\right]x_{i}\]

for observations \(i=1,...,n\)

Where \(q=2y-1\). This simplification comes from the fact that the normal distribution is symmetric.