3 packages on CRAN
Imputation of missing values in datasets of ordinal variables through a forward imputation algorithm
Two methods based on the Forward Imputation approach are implemented for the imputation of quantitative missing data. One method alternates Nearest Neighbour Imputation and Principal Component Analysis (function 'ForImp.PCA'), the other uses Nearest Neighbour Imputation with the Mahalanobis distance (function 'ForImp.Mahala').
A gaussian copula based procedure for generating samples from discrete random variables with prescribed correlation matrix and marginal distributions.