statsmodels.discrete.count_model.ZeroInflatedNegativeBinomialResults.get_influence¶

ZeroInflatedNegativeBinomialResults.get_influence()¶

Influence and outlier measures

See notes section for influence measures that do not apply for zero inflated models.

Returns:¶

MLEInfluence

The instance has methods to calculate the main influence and outlier measures as attributes.

See also

statsmodels.stats.outliers_influence.MLEInfluence

Notes

ZeroInflated models have functions that are not differentiable with respect to sample endog if endog=0. This means that generalized leverage cannot be computed in the usual definition.

Currently, both the generalized leverage, in hat_matrix_diag attribute and studetized residuals are not available. In the influence plot generalized leverage is replaced by a hat matrix diagonal that only takes combined exog into account, computed in the same way as for OLS. This is a measure for exog outliers but does not take specific features of the model into account.