In the framework of data imputation, this paper provides a non-parametric approach to missing data imputation based on Information Retrieval. In particular, an incremental procedure based on the iterative use of a tree-based method is proposed and a suitable Incremental Imputation Algorithm is introduced. The key idea is to define a lexicographic ordering of cases and variables so that conditional mean imputation via binary trees can be performed incrementally. A simulation study and real world applications are shown to describe the advantages and the good performance with respect to standard approaches
Incremental Tree-Based Imputation with lexicographic ordering
CONVERSANO, CLAUDIO;
2003-01-01
Abstract
In the framework of data imputation, this paper provides a non-parametric approach to missing data imputation based on Information Retrieval. In particular, an incremental procedure based on the iterative use of a tree-based method is proposed and a suitable Incremental Imputation Algorithm is introduced. The key idea is to define a lexicographic ordering of cases and variables so that conditional mean imputation via binary trees can be performed incrementally. A simulation study and real world applications are shown to describe the advantages and the good performance with respect to standard approaches
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