Statistical analysis with missing data
Statistical analysis with missing data
GRAFT, a complete system for data fusion
Computational Statistics & Data Analysis
Uncertainty analysis for statistical matching of ordered categorical variables
Computational Statistics & Data Analysis
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A new matching procedure based on imputing missing data by means of a local linear estimator of the underlying population regression function (that is assumed not necessarily linear) is introduced. Such a procedure is compared to other traditional approaches, more precisely hot deck methods as well as methods based on kNN estimators. The relationship between the variables of interest is assumed not necessarily linear. Performance is measured by the matching noise given by the discrepancy between the distribution generating genuine data and the distribution generating imputed values.