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Model Selection in a Composite Likelihood Framework Based on Density Power Divergence
Elena Castilla1, Nirian Martín2, Leandro Pardo1
1Interdisciplinary Mathematics Institute and Department of Statistics and O.R. I, Complutense University of Madrid, 28040 Madrid, Spain.
Abstract:
This paper presents a model selection criterion in a composite likelihood framework based on density power divergence measures and in the composite minimum density power divergence estimators, which depends on an tuning parameter α . After introducing such a criterion, some asymptotic properties are established. We present a simulation study and two numerical examples in order to point out the robustness properties of the introduced model selection criterion.
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