In the framework of incomplete data analysis, this paper provides a nonparametric approach to missing data imputation based on Information Retrieval. In particular, an incremental procedure based on the iterative use of 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 data applications are carried out to describe the advantages and the performance with respect to standard approaches.
Incremental tree-based missing data imputation with lexicographic ordering / Conversano, C.; Siciliano, Roberta. - In: JOURNAL OF CLASSIFICATION. - ISSN 0176-4268. - STAMPA. - 26:3(2009), pp. 361-379. [10.1007/s00357-009-9038-8]
Incremental tree-based missing data imputation with lexicographic ordering
SICILIANO, ROBERTA
2009
Abstract
In the framework of incomplete data analysis, this paper provides a nonparametric approach to missing data imputation based on Information Retrieval. In particular, an incremental procedure based on the iterative use of 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 data applications are carried out to describe the advantages and the performance with respect to standard approaches.File | Dimensione | Formato | |
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