Model Selection in a Composite Likelihood Framework Based on Density Power Divergence Academic Article uri icon

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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.

publication date

  • February 27, 2020