Probit model Hessian matrix of the log-likelihood
Parameters: | params : array-like
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Returns: | The Hessian evaluated at `params` : |
Notes
\frac{\partial^{2}\ln L}{\partial\beta\partial\beta^{\prime}}=-\lambda_{i}\left(\lambda_{i}+x_{i}^{\prime}\beta\right)x_{i}x_{i}^{\prime}
where .. math:: lambda_{i}=frac{q_{i}phileft(q_{i}x_{i}^{prime}betaright)}{Phileft(q_{i}x_{i}^{prime}betaright)}
and q=2y-1