Data Fusion consists of merging information coming from two different surveys. The first is “donor survey” while the second is “receptor survey”. The aim is to complete the receptor matrix exploiting information acquired from the donor matrix. The proposed method allows to impute the missing information into the second survey through a mix of the two different methodologies proposed in literature: Explicit model-based estimation and Implicit models for imputation.

A double imputation method for Data Fusion

PISCITELLI, ALFONSO
2008

Abstract

Data Fusion consists of merging information coming from two different surveys. The first is “donor survey” while the second is “receptor survey”. The aim is to complete the receptor matrix exploiting information acquired from the donor matrix. The proposed method allows to impute the missing information into the second survey through a mix of the two different methodologies proposed in literature: Explicit model-based estimation and Implicit models for imputation.
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/11588/429813
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact