This article proposes the use of the Bayesian reference analysis to estimate the parameters of the generalized normal linear regression model. It is shown that the reference prior led to a proper posterior distribution, while the Jeffreys prior returned an improper one. The inferential purposes were obtained via Markov Chain Monte Carlo (MCMC). Furthermore, diagnostic techniques based on the Kullback–Leibler divergence were used. The proposed method was illustrated using artificial data and real data on the height and diameter of Eucalyptus clones from Brazil.

中文翻译：

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广义正态线性回归模型的贝叶斯参考分析

本文提出使用贝叶斯参考分析来估计广义正态线性回归模型的参数。结果表明，参考先验导致正确的后验分布，而杰弗里斯先验则返回了不合适的后验分布。推论目的是通过马尔可夫链蒙特卡罗（MCMC）获得的。此外，使用了基于Kullback-Leibler散度的诊断技术。使用人工数据和来自巴西的桉树无性系的高度和直径的真实数据说明了该方法。