论文标题
带有普通内核及其应用的多变量日志分布
Multivariate Log-Skewed Distributions with normal kernel and their Applications
论文作者
论文摘要
我们介绍了两类具有正常内核的多元日志偏斜分布：日志规范基本偏斜 - 正常（log-cfusn）和日志统一偏度偏差正常（log-sun）。我们还讨论了log-cfusn分布家族的某些属性。这些新的对数分配的新类别包括对数正态和多变量log-skew普通族的特定情况。我们讨论了一些与贝叶斯推断有关的分布家族中的贝叶斯推断有关的问题，主要是我们重点介绍如何对偏斜参数的先前不确定性进行建模。基于log-fusn家族的随机表示，我们提出了一种数据增强策略，以从后验分布中进行采样。该拟议的家庭用于分析美国国家月度降水数据。我们得出的结论是，高维偏斜功能会导致更好的模型拟合。
We introduce two classes of multivariate log skewed distributions with normal kernel: the log canonical fundamental skew-normal (log-CFUSN) and the log unified skew-normal (log-SUN). We also discuss some properties of the log-CFUSN family of distributions. These new classes of log-skewed distributions include the log-normal and multivariate log-skew normal families as particular cases. We discuss some issues related to Bayesian inference in the log-CFUSN family of distributions, mainly we focus on how to model the prior uncertainty about the skewing parameter. Based on the stochastic representation of the log-CFUSN family, we propose a data augmentation strategy for sampling from the posterior distributions. This proposed family is used to analyze the US national monthly precipitation data. We conclude that a high dimensional skewing function lead to a better model fit.
