statsmodels.discrete.discrete_model.Logit.hessian¶
- Logit.hessian(params)[source]¶
Logit model Hessian matrix of the log-likelihood
- Parameters:
- paramsarray_like
The parameters of the model
- Returns:
- hess
ndarray, (k_vars,k_vars) The Hessian, second derivative of loglikelihood function, evaluated at params
- hess
Notes
\[\frac{\partial^{2}\ln L}{\partial\beta\partial\beta^{\prime}}=-\sum_{i}\Lambda_{i}\left(1-\Lambda_{i}\right)x_{i}x_{i}^{\prime}\]