statsmodels.discrete.discrete_model.Logit.hessian

Logit.hessian(params) [source]

Logit model Hessian matrix of the log-likelihood

Parameters:	params (array-like) – The parameters of the model
Returns:	hess – The Hessian, second derivative of loglikelihood function, evaluated at params
Return type:	ndarray, (k_vars, k_vars)

Notes

\[\frac{\partial^{2}\ln L}{\partial\beta\partial\beta^{\prime}}=-\sum_{i}\Lambda_{i}\left(1-\Lambda_{i}\right)x_{i}x_{i}^{\prime}\]