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.
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