On the occasional exactness of the distributional transform approximation for direct Gaussian copula models with discrete margins

John Hughes

Statistics & Probability Letters, 2021, vol. 177, issue C

Abstract: The direct Gaussian copula model with discrete margins is appealing but poses computational challenges due to its intractable likelihood. We show that the distributional transform-based approximate likelihood is essentially exact for some variants of the model, and we propose a quantity that can be used to assess exactness for a given dataset.

Keywords: Bartlett identity; Gaussian copula; Intractable likelihood; Model assessment; Monte Carlo statistical method (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1016/j.spl.2021.109159

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