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