summary_estimates_table#

er_evaluation.estimators.summary_estimates_table(sample, weights, predictions, names=None)[source]#

Generate a summary estimates table for the given sample, weights, predictions, and names.

Parameters:

  • sample (Series) – Membership vector indexed by cluster elements and with values corresponding to associated cluster identifier.

  • weights (Series) – Pandas Series indexed by cluster identifier and with values corresponding to cluster sampling weights (e.g., inverse sampling probabilities). Can also be the string “uniform” for uniform sampling weights, or “cluster_size” for inverse cluster size sampling weights.

  • predictions (Dict) – Dictionary of membership vectors.

  • names (pd.Series, optional) – Series containing names associated with each cluster element. Used for Name Variation and Homonymy Rate Estimates. Defaults to None.

Returns:

Pandas DataFrame with columns “prediction”, “estimate”, “value”, and “std”, where value and std are the point estimate and standard deviation estimate for the estimator applied to the given sample, sampling weights, prediction, and names.

Return type:

DataFrame