On the non-identifiability of unified skew-normal distributions

Kesen Wang, Reinaldo B. Arellano-Valle, Adelchi Azzalini, Marc G. Genton

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


We investigate the non-identifiability of the multivariate unified skew-normal distribution under permutation of its latent variables. We show that the non-identifiability issue also holds with other parameterizations and extends to the family of unified skew-elliptical distributions and more generally to selection distributions. We provide several suggestions to make the unified skew-normal model identifiable and describe various sub-models that are identifiable.
Original languageEnglish (US)
Issue number1
StatePublished - Jul 17 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-07-28
Acknowledgements: The research of Kesen Wang and Marc G. Genton was supported by the King Abdullah University of Science and Technology (KAUST).


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