Man pages for VIM
Visualization and Imputation of Missing Values
| aggr | Aggregations for missing/imputed values |
| alphablend | Alphablending for colors |
| Animals_na | Animals_na |
| barMiss | Barplot with information about missing/imputed values |
| bcancer | Breast cancer Wisconsin data set |
| bgmap | Backgound map |
| bootstrap_resample | Bootstrap resampling with robust strategies |
| brittleness | Brittleness index data set |
| build_gam_formula | Build a GAM formula with automatic smooth terms |
| cellIRWLS | Cell-weighted Iteratively Reweighted Least Squares |
| cellWeights | Compute per-cell contamination weights |
| cellWeightsFromResiduals | Compute cell weights from regression residuals |
| cellWeightsMCD | Compute per-cell weights using MCD-based conditional... |
| chorizonDL | C-horizon of the Kola data with missing values |
| colic | Colic horse data set |
| collisions | Subset of the collision data |
| colormapMiss | Colored map with information about missing/imputed values |
| colSequence | HCL and RGB color sequences |
| complete_model_info | Complete model diagnostics from learner predictions when the... |
| countInf | Count number of infinite or missing values |
| diabetes | Synthetic Pima Indians Diabetes Data |
| dot-apply_weight_fun | Apply a weight function to standardized values |
| dot-robust_scale | Robust scale estimate via MAD |
| dot-weighted_qr_solve | QR-based weighted least squares with cell-derived row weights |
| evaluation | Error performance measures |
| extract_model_info | Extract model diagnostics for bootstrap strategies |
| food | Food consumption |
| gapMiss | Missing value gap statistics |
| gowerD | Computes the extended Gower distance of two data sets |
| growdotMiss | Growing dot map with information about missing/imputed values |
| histMiss | Histogram with information about missing/imputed values |
| hotdeck | Hot-Deck Imputation |
| huber_weight | Huber weight function |
| impPCA | Iterative EM PCA imputation |
| imputeCellEM | Cellwise-robust EM imputation for mixed data |
| imputeCellIRMI | Cellwise-robust iterative regression imputation for mixed... |
| imputeCellM | Cellwise M-estimation imputation |
| imputeCellMCD | Cellwise MCD-based imputation for mixed data |
| imputeCellMM | Cell-weighted MM imputation for mixed data (Path A) |
| imputeCellReg | Cellwise-robust regression imputation for mixed data |
| imputeCellwise | Unified cellwise-robust imputation dispatcher |
| imputeRobust | Robust imputation |
| imputeRobustChain | FUNCTION_TITLE |
| initialise | Initialization of missing values |
| inject_uncertainty | Inject imputation uncertainty into predictions |
| irmi | Iterative robust model-based imputation (IRMI) |
| kNN | k-Nearest Neighbour Imputation |
| kola.background | Background map for the Kola project data |
| lse_synthetic | Synthetic Austrian Structural Business Survey data |
| lse_synthetic_rules | Validation rules for the synthetic LSE data |
| makeMissing | Generate MCAR/MAR/MNAR missingness in complete data |
| mapMiss | Map with information about missing/imputed values |
| marginmatrix | Marginplot Matrix |
| marginplot | Scatterplot with additional information in the margins |
| matchImpute | Fast matching/imputation based on categorical variable |
| matrixplot | Matrix plot |
| maxCat | Aggregation function for a factor variable |
| medianSamp | Aggregation function for a ordinal variable |
| midastouch_donors | Midastouch: PMM with covariate-distance-weighted donor... |
| mosaicMiss | Mosaic plot with information about missing/imputed values |
| new_vimmi | Constructor for vimmi objects |
| oob_predictions | Out-of-bag predictions of a fitted learner, when it exposes... |
| overimpute | Overimputation: calibration diagnostic for an imputation... |
| pairsVIM | Scatterplot Matrices |
| parcoordMiss | Parallel coordinate plot with information about... |
| pbox | Parallel boxplots with information about missing/imputed... |
| plot.vimmi | Diagnostic plots for a vimmi object |
| pmm_donor_selection | Score-based PMM donor selection |
| pmm_observed_scores | Predicted donor scores for true PMM |
| prepare | Transformation and standardization |
| pulplignin | Pulp lignin content |
| rangerImpute | Random Forest Imputation |
| register_gam_learners | Register GAM-based mlr3 learners for vimpute |
| register_vimpute_method | Register an imputation method for 'vimpute()' |
| regressionImp | Regression Imputation (via vimpute) |
| rugNA | Rug representation of missing/imputed values |
| sampleCat | Random aggregation function for a factor variable |
| SBS5242 | Synthetic subset of the Austrian structural business... |
| scattJitt | Bivariate jitter plot |
| scattmatrixMiss | Scatterplot matrix with information about missing/imputed... |
| scattMiss | Scatterplot with information about missing/imputed values |
| sleep | Mammal sleep data |
| spineMiss | Spineplot with information about missing/imputed values |
| tableMiss | create table with highlighted missings/imputations |
| tao | Tropical Atmosphere Ocean (TAO) project data |
| testdata | Simulated data set for testing purpose |
| toydataMiss | Simulated toy data set for examples |
| tukey_weight | Tukey bisquare weight function |
| unregister_vimpute_method | Remove a user-registered 'vimpute()' method |
| unwrap_raw_model | Unwrap a fitted mlr3 learner to its underlying model object |
| vim_as_mids | Convert a vimmi object to a mice mids object |
| vim_complete | Extract completed datasets from a vimmi object |
| vimmi | VIM Multiple Imputations (vimmi) |
| VIM-package | The VIM Package: Visualization and Imputation of Missing... |
| vimpute | Impute missing values with prefered model, sequentially, with... |
| vimpute_methods | List the imputation methods registered for 'vimpute()' |
| vimpute_search_space | The built-in tuning search space of a learner |
| vimpute_spec | Per-variable imputation specification for 'vimpute()' |
| vimpute_tune_control | Control the hyperparameter tuning of 'vimpute()' |
| wine | Wine tasting and price |
| with.vimmi | Evaluate an expression across all imputations |
| xgboostImpute | Xgboost Imputation |
