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