statsmodels.discrete.discrete_model.Poisson.hessian

Poisson.hessian(params) [source]

Poisson model Hessian matrix of the loglikelihood

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

\[\frac{\partial^{2}\ln L}{\partial\beta\partial\beta^{\prime}}=-\sum_{i=1}^{n}\lambda_{i}x_{i}x_{i}^{\prime}\]

where the loglinear model is assumed

\[\ln\lambda_{i}=x_{i}\beta\]