statsmodels.discrete.discrete_model.Probit.loglikeobs¶

Probit.loglikeobs(params)[source]¶

Log-likelihood of probit model for each observation

Parameters:¶

paramsarray_like

The parameters of the model.

Returns:¶

loglikearray_like

The log likelihood for each observation of the model evaluated at params. See Notes

Notes

$$\ln L_i=\ln \mathrm{\Phi }\left(q_i{x}_i^{\prime }\beta \right)$$

for observations $i=1,...,n$

where $q=2y-1$. This simplification comes from the fact that the normal distribution is symmetric.