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We present a proposal to deal with the non-normality issue in the context ofregression models with measurement errors when both the response and theexplanatory variable are observed with error. We extend the normal model byjointly modeling the unobserved covariate and the random errors by a finitemixture of scale mixture of skew-normal distributions. This approach allows usto model data with great flexibility, accommodating skewness, heavy tails, andmulti-modality.

Bayesian Measurement Error Models Using Finite Mixtures of Scale Mixtures of Skew-Normal Distributions