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
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/7691
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact