Logit model Jacobian of the log-likelihood for each observation
params: array-like :
The parameters of the model
jac : ndarray, (nobs, k)
The derivative of the loglikelihood evaluated at params for each observation
Notes
\frac{\partial\ln L}{\partial\beta}=\sum_{i=1}^{n}\left(y_{i}-\Lambda_{i}\right)x_{i}
statsmodels.discrete.discrete_model.Logit.initialize
statsmodels.discrete.discrete_model.Logit.loglike
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