/Statsmodels

# statsmodels.discrete.discrete_model.Logit.loglikeobs

Logit.loglikeobs(params) [source]

Log-likelihood of logit model for each observation.

Parameters: params (array-like) – The parameters of the logit model. loglike – The log likelihood for each observation of the model evaluated at params. See Notes ndarray

#### 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.