Statistical Matching or Data Fusion

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Documentation for package ‘StatMatch’ version 1.4.3

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StatMatch-package Statistical Matching or Data Fusion
comb.samples Statistical Matching of data from complex sample surveys
comp.cont Compares two distributions of the same continuous variable
comp.prop Compares two distributions of the same categorical variable
create.fused Creates a matched (synthetic) dataset
create.imputed Fills-in missing values in the recipient dataset with values observed on the donors units
fact2dummy Transforms a categorical variable in a set of dummy variables
Fbounds.pred Estimates Frechet bounds for cells in the contingency table crossing two categorical variables observed in distinct samples referred to the same target population.
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
plotBounds Graphical representation of the uncertainty bounds estimated through the 'Frechet.bounds.cat' function
plotCont graphical comparison of the estimated distributions for the same continuous variable.
plotTab Graphical comparison of the estimated distributions for the same categorical variable.
pw.assoc Pairwise measures between categorical variables
RANDwNND.hotdeck Random Distance hot deck.
rankNND.hotdeck Rank distance hot deck method.
rho.bounds Estimates plausible values of the Pearson's correlation coefficient between two variables observed in distinct samples referred to the same target population.
rho.bounds.pred Estimates plausible values of the Pearson's correlation coefficient between two variables observed in distinct samples referred to the same target population.
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
selMtc.by.unc Identifies the best combination if matching variables in reducing uncertainty in estimation the contingency table Y vs. Z.
StatMatch Statistical Matching or Data Fusion