Article ID Journal Published Year Pages File Type
417177 Computational Statistics & Data Analysis 2008 12 Pages PDF
Abstract

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.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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