论文标题
贝叶斯测量误差模型，使用偏斜正常分布的比例混合物的有限混合物
Bayesian Measurement Error Models Using Finite Mixtures of Scale Mixtures of Skew-Normal Distributions
论文作者
论文摘要
我们提出了一项建议，以在回归模型的背景下以测量误差的方式处理非正常性问题，当响应和解释变量均以错误观察到。我们通过共同对未观察到的协变量和随机误差进行共同模拟偏斜正常分布的比例混合物的有限混合物来扩展正常模型。这种方法使我们能够以极大的灵活性对数据进行建模，可容纳偏度，沉重的尾巴和多模式。
We present a proposal to deal with the non-normality issue in the context of regression models with measurement errors when both the response and the explanatory variable are observed with error. We extend the normal model by jointly modeling the unobserved covariate and the random errors by a finite mixture of scale mixture of skew-normal distributions. This approach allows us to model data with great flexibility, accommodating skewness, heavy tails, and multi-modality.
