statsmodels.discrete.discrete_model.Logit.loglikeobs¶

Logit.loglikeobs(params)[source]¶

Log-likelihood of logit model for each observation.

Parameters:¶

paramsarray_like

The parameters of the logit model.

Returns:¶

loglikendarray

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

Notes

$$\ln L=\sum _i\ln \mathrm{\Lambda }\left(q_i{x}_i^{\prime }\beta \right)$$

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

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