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  • 标题:Modelling location, scale and shape parameters of the Birnbaum-Saunders generalized t distribution
  • 本地全文:下载
  • 作者:Luiz R. Nakamura ; Robert A. Rigby ; Dimitrios M. Stasinopoulos
  • 期刊名称:Journal of Data Science
  • 印刷版ISSN:1680-743X
  • 电子版ISSN:1683-8602
  • 出版年度:2017
  • 卷号:15
  • 期号:2
  • 页码:221-238
  • 出版社:Tingmao Publish Company
  • 摘要:The Birnbaum-Saunders generalized t (BSGT) distribution is a very flflexible family of distributions that admits different degrees of skewness and kurtosis and includes some important special or limiting cases available in the literature, such as the Birnbaum-Saunders and Birnbaum-Saunders t distributions. In this paper we provide a regression type model to the BSGT distribution based on the generalized additive models for location, scale and shape (GAMLSS) framework. The resulting model has high flflexibility and therefore a great potential to model the distribution parameters of response variables that present light or heavy tails, i.e. platykurtic or leptokurtic shapes, as functions of explanatory variables. For different parameter settings, some simulations are performed to investigate the behavior of the estimators. The potentiality of the new regression model is illustrated by means of a real motor vehicle insurance data set.
  • 关键词:Finance; GAMLSS; generalized additive models; penalized splines; positively skewed data.
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