statsmodels.discrete.discrete_model.Logit.hessian

Logit.hessian(params)

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

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