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EnglishIn 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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| Titolo: | Incremental Tree-Based Imputation with lexicographic ordering | |
| Autori: | ||
| Data di pubblicazione: | 2003 | |
| 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 | |
| Handle: | http://hdl.handle.net/11584/7691 | |
| ISBN: | 1-886658-09-9 | |
| Tipologia: | 2.1 Contributo in volume (Capitolo o Saggio) |
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