Multivariate Log-Skewed Distributions with normal kernel and their Applications
| Autor: | de Queiroz, Marina M., Loschi, Rosangela H., Silva, Roger W. C. |
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| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Statistics (Berlin), 2016 |
| Druh dokumentu: | Working Paper |
| Popis: | 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. Comment: 20 pages |
| Databáze: | arXiv |
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