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Correction of Incoherences in Statistical Matching

  • Andrea CapotortiEmail author
  • Barbara Vantaggi
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

Statistical matching is studied inside a coherent setting, by focusing on the problem of removing inconsistencies. When structural zeros among involved variables are present, incoherencies on the parameter estimations can arise. The aim is to compare different methods to remove such incoherences based on specific pseudo-distances. The comparison is given through an exemplifying example of 100 simulations from a known population with three categorical variables, that carries out to the light peculiarities of the statistical matching problem.

Keywords

Statistical Match Joint Probability Distribution Leibler Divergence Bregman Divergence Structural Zero 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Dip. Matematica e InformaticaUniversitá di PerugiaPerugiaItaly
  2. 2.Dip. Scienze di Base e Applicate per l’IngegneriaUniversitá La SapienzaRomaItaly

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