statsmodels.discrete.discrete_model.Logit.score_obs¶

Logit.score_obs(params)[source]¶

Logit model Jacobian of the log-likelihood for each observation

Parameters:¶

params : array_like¶

The parameters of the model

Returns:¶

jac – The derivative of the loglikelihood for each observation evaluated at params.

Return type:¶

array_like

Notes

\[\frac{\partial\ln L_{i}}{\partial\beta}=\left(y_{i}-\Lambda_{i}\right)x_{i}\]

for observations \(i=1,...,n\)