On the non‐identifiability of unified skew‐normal distributions
Copyright policy )On the non‐identifiability of unified skew‐normal distributions
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.
570, 330, Statistics, Probability (math.PR), Mathematics - Statistics Theory, Statistics Theory (math.ST), permutation, selection distribution, unified skew-elliptical distribution, non-identifiability, FOS: Mathematics, latent variable, Mathematics - Probability, unified skew-normal distribution
570, 330, Statistics, Probability (math.PR), Mathematics - Statistics Theory, Statistics Theory (math.ST), permutation, selection distribution, unified skew-elliptical distribution, non-identifiability, FOS: Mathematics, latent variable, Mathematics - Probability, unified skew-normal distribution
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