Random Distance hot deck.
Statistical Matching or Data Fusion
Statistical Matching of data from complex sample surveys
Frechet bounds of cells in a contingency table
Creates a matched (synthetic) dataset
Computes the Frechet bounds of cells in a contingency table by considering all the possible subsets of the common variables.
Empirical comparison of two estimated distributions of the same continuous variable
Compares two distributions of the same categorical variable
Identifies the best combination if matching variables in reducing uncertainty in estimation the contingency table Y vs. Z.
Distance Hot Deck method.
Computes the Mahalanobis Distance
Harmonizes the marginal (joint) distribution of a set of variables observed independently in two sample surveys referred to the same target population
Computes the Gower's Distance
Graphical representation of the uncertainty bounds estimated through the Frechet.bounds.cat
function
Pseudo-Bayes estimates of cell probabilities
Transforms a categorical variable in a set of dummy variables
graphical comparison of the estimated distributions for the same continuous variable.
Statistical Matching via Mixed Methods
Rank distance hot deck method.
Fills-in missing values in the recipient dataset with values observed on the donors units
Computes the Maximum Distance
Artificial data set resembling EU--SILC survey
Artificial data set resembling EU--SILC survey
Artificial data set resembling EU--SILC survey
Pairwise measures between categorical variables
Graphical comparison of the estimated distributions for the same categorical variable.