| StatMatch-package | Statistical Matching or Data Fusion |
| comb.samples | Statistical Matching of data from complex sample surveys |
| comp.prop | Compares two distributions of categorical variables |
| create.fused | Creates a matched (synthetic) dataset |
| fact2dummy | Transforms a categorical variable in a set of dummy variables |
| Fbwidths.by.x | Computes the Frechet bounds of cells in a contingency table by considering all the possible subsets of the common variables. |
| Frechet.bounds.cat | Frechet bounds of cells in a contingency table |
| gower.dist | Computes the Gower's Distance |
| harmonize.x | Harmonizes the marginal (joint) distribution of a set of variables observed independently in two sample surveys referred to the same target population |
| mahalanobis.dist | Computes the Mahalanobis Distance |
| maximum.dist | Computes the Maximum Distance |
| mixed.mtc | Statistical Matching via Mixed Methods |
| NND.hotdeck | Distance Hot Deck method. |
| pBayes | Pseudo-Bayes estimates of cell probabilities |
| pw.assoc | Pairwise association measure between categorical variables |
| RANDwNND.hotdeck | Random Distance hot deck. |
| rankNND.hotdeck | Rank distance hot deck method. |
| samp.A | Artificial data set resembling EU-SILC survey |
| samp.B | Artificial data set resembling EU-SILC survey |
| samp.C | Artificial data set resembling EU-SILC survey |
| StatMatch | Statistical Matching or Data Fusion |