期刊
JOURNAL OF APPLIED STATISTICS
卷 38, 期 8, 页码 1633-1649出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/02664763.2010.515679
关键词
EM algorithm; extreme percentiles; local influence; sinh-normal distribution; skew-normal distribution
资金
- CNPq from Brazil
- FAPESP from Brazil
- FONDECYT from Chile [1080326]
- DIPUV from Chile [50-2007]
In this paper, we propose a method to assess influence in skew-Birnbaum-Saunders regression models, which are an extension based on the skew-normal distribution of the usual Birnbaum-Saunders (BS) regression model. An interesting characteristic that the new regression model has is the capacity of predicting extreme percentiles, which is not possible with the BS model. In addition, since the observed likelihood function associated with the new regression model is more complex than that from the usual model, we facilitate the parameter estimation using a type-EM algorithm. Moreover, we employ influence diagnostic tools that considers this algorithm. Finally, a numerical illustration includes a brief simulation study and an analysis of real data in order to show the proposed methodology.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据