Two-piece location-scale models are used for modeling data presenting departures from symmetry. In this paper, we propose an objective Bayesian methodology for the tail parameter of two particular distributions of the above family: the skewed exponential power distribution and the skewed generalised logistic distribution. We apply the proposed objective approach to time series models and linear regression models where the error terms follow the distributions object of study. The performance of the proposed approach is illustrated through simulation experiments and real data analysis. The methodology yields improvements in density forecasts, as shown by the analysis we carry out on the electricity prices in Nordpool markets.

中文翻译：

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基于损失的两部分式位置比例分布方法，并应用于相关数据

两件式位置比例模型用于对表示对称性偏离的数据进行建模。在本文中，我们针对上述族的两个特定分布的尾参数提出了一种客观的贝叶斯方法：偏指数幂分布和偏广义逻辑分布。我们将提出的客观方法应用于时间序列模型和线性回归模型，其中误差项遵循研究的分布对象。通过仿真实验和实际数据分析说明了该方法的性能。正如我们对诺德普尔市场电价所做的分析所表明的那样，该方法可以提高密度预测。