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Logit.score_obs()

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 : ndarray, (nobs, k_vars)

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

doc_statsmodels
doc_statsmodels
2017-01-18 16:11:43
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