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首页> 外文期刊>Journal of Modern Applied Statistical Methods >Robust Predictive Inference for Multivariate Linear Models with Elliptically Contoured Distribution Using Bayesian, Classical and Structural Approaches
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Robust Predictive Inference for Multivariate Linear Models with Elliptically Contoured Distribution Using Bayesian, Classical and Structural Approaches

机译:使用贝叶斯,古典和结构方法具有椭圆形轮廓分布的多变量线性模型的强大预测推理

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摘要

Predictive distributions of future response and future regression matrices under multivariate elliptically contoured distributions are discussed. Under the elliptically contoured response assumptions, these are identical to those obtained under matric normal or matric-t errors using structural, Bayesian with improper prior, or classical approaches. This gives inference robustness with respect to departure from the reference case of independent sampling from the matric normal or matric t to multivariate elliptically contoured distributions. The importance of the predictive distribution for skewed elliptical models is indicated; the elliptically contoured distribution, as well as matric t distribution, have significant applications in statistical practices.
机译:讨论了多元椭圆形分布下未来响应和未来回归矩阵的预测分布。 在椭圆形的响应假设下,这些与使用结构,贝叶斯的Matric正常或Matric-T误差下获得的那些相同,具有不正确的先前或经典方法。 这对从Matric正常或Matric T的独立采样的参考情况偏离偏离的推理稳健性,以使多变量椭圆形状分布。 指出了偏斜椭圆模型预测分布的重要性; 椭圆形的分布以及Matric T分布在统计实践中具有重要应用。

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