文章基本信息

标题：Reparameterized Birnbaum-Saunders regression models with varying precision
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作者：Manoel Santos-Neto ; Francisco José A. Cysneiros ; Víctor Leiva 等
期刊名称：Electronic Journal of Statistics
印刷版ISSN：1935-7524
出版年度：2016
卷号：10
期号：2
页码：2825-2855
DOI：10.1214/16-EJS1187
语种：English
出版社：Institute of Mathematical Statistics
摘要：We propose a methodology based on a reparameterized Birnbaum-Saunders regression model with varying precision, which generalizes the existing works in the literature on the topic. This methodology includes the estimation of model parameters, hypothesis tests for the precision parameter, a residual analysis and influence diagnostic tools. Simulation studies are conducted to evaluate its performance. We apply it to two real-world case-studies to show its potential with the R software.