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.
A Further Empirical Study on the Over-Performance of Estimate Correction in Statistical Matching
CAPOTORTI, Andrea
2012
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.File in questo prodotto:
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