# 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

$\ln L=\sum_{i}\ln\Lambda \left(q_{i}x_{i}^{\prime}\beta\right)$

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

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