statsmodels.stats.sandwich_covariance.cov_cluster#
- statsmodels.stats.sandwich_covariance.cov_cluster(results, group, use_correction=True, crv_type='cluster')[source]#
Cluster robust covariance matrix
Calculates sandwich covariance matrix for a single cluster, i.e., grouped variables.
- Parameters:
- results
resultinstance result of a regression, uses results.model.exog and results.resid TODO: this should use wexog instead
- grouparray_like
ofint Integer-valued index of clusters or groups.
- use_correctionbool,
optional If true (default), then the small sample correction factor is used.
- crv_type{“cluster”, “cluster-crv3”, “cluster-jk”},
optional If ‘cluster’ (default), compute a CRV1 robust variance covariance matrix. If ‘cluster-crv3’, compute a CRV3 robust variance covariance matrix. If ‘cluster-jk’, compute a variance covariance matrix via the cluster jackknife.
- results
- Returns:
- cov
ndarray, (k_vars,k_vars) cluster robust covariance matrix for parameter estimates
- cov
Notes
same result as Stata in UCLA example and same as Peterson