statsmodels.stats.outliers_influence.MLEInfluence.resid_score¶
- MLEInfluence.resid_score(joint=True, index=None, studentize=False)[source]¶
Score observations scaled by inverse hessian.
Score residual in resid_score are defined in analogy to a score test statistic for each observation.
- Parameters:¶
- jointbool
If joint is true, then a quadratic form similar to score_test is returned for each observation. If joint is false, then standardized score_obs are returned. The returned array is two-dimensional
- index
ndarray(optional) Optional index to select a subset of score_obs columns. By default, all columns of score_obs will be used.
- studentizebool
If studentize is true, the the scaled residuals are also studentized using the generalized leverage.
- Returns:¶
- array1-D or 2-D
residuals
- array1-D or 2-D
Notes
Status: experimental
Because of the one srep approacimation of d_params, score residuals are identical to cooks_distance, except for
cooks_distance is normalized by the number of parameters
cooks_distance uses cov_params, resid_score is based on Hessian. This will make them differ in the case of robust cov_params.