statsmodels.discrete.discrete_model.Logit.score_obs¶
- Logit.score_obs(params)[source]¶
 Logit model Jacobian of the log-likelihood for each observation
- Parameters:¶
 - paramsarray_like
 The parameters of the model
- Returns:¶
 - jacarray_like
 The derivative of the loglikelihood for each observation evaluated at params.
Notes
\[\frac{\partial\ln L_{i}}{\partial\beta}=\left(y_{i}-\Lambda_{i}\right)x_{i}\]for observations \(i=1,...,n\)
  
    
      Last update:
      Jun 10, 2024