Introduction | Installation | Preparing data | Imputation Function | Calculating the energy-I-Score | Important parameters | Number of imputations: N | Limiting the number of scored variables: max_length | Handling incomplete training sets: skip_if_needed | Scaling variables: scale | Energy-I-Score for mixed data | Calculating the DR-I-Score | Parameters | Comparing multiple imputation methods | Comparing methods using multiple scores | Summary of best practices | Energy score | References

Introduction | Notation | Algorithm Overview | Step 1: Selection of Predictor Set | Step 2: Data Partitioning | Step 3: Multiple Imputations | Step 4: Energy Distance Calculation | For each $i \in L_j$, the energy-I-Score component is computed as:[\widehat{S}^j_{\mathrm{NA}}(H,P) =\frac{1}{|L_j|} \sum_{i \in L_j}\left[\frac{1}{2N^2} \sum_{l=1}^N \sum_{\ell=1}^N|\tilde{X}{i,j}^{(l)} - \tilde{X}{i,j}^{(\ell)}| | Step 5: Weighting | Step 6: Final Score | Practical Interpretation | References