Abstract
Usual estimates inside the statistical matching problem can encounter consistency problem whenever logical constraints are present among categorical variables. Inconsistencies correction through a specific discrepancy minimization has already shown, in terms of goodness-of-fit test, an empirical over-performance with respect to originally coherent assessments. This behavior is now confirmed also with respect to distances between imprecise estimates and imprecise models represented by credal sets of joint distributions.
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Capotorti, A. (2012). A Further Empirical Study on the Over-Performance of Estimate Correction in Statistical Matching. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 300. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31724-8_14
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DOI: https://doi.org/10.1007/978-3-642-31724-8_14
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