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