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dc.contributor.advisor谭忠
dc.contributor.author蔡庆淞
dc.date.accessioned2018-12-05T01:40:26Z
dc.date.available2018-12-05T01:40:26Z
dc.date.issued2017-12-27
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/170068
dc.description.abstract本文主要研究混合双参数广义Pareto分布模型(下面简称混合广义Pareto模型)的概率密度估计。混合模型能够非常好地拟合现实数据。Pareto分布的特点是有厚尾特征,所以在金融风险度量方面受到越来越多的重视。与此同时,在保险、可靠性分析等方面应用十分普遍。实际运用中经常有需要用到多成分混合广义pareto模型的情况。 本文选取实际运用最广泛的一类广义pareto分布进行研究。在采取传统的矩估计和极大似然估计对混合分布进行参数估计时,发现它们确实在理论上很好实现,但是在实际计算中却特别繁琐。EM算法是常用的估计参数隐变量的利器,是一种迭代算法,经常被用来解决极大似然估计。它能够从非完整数...
dc.description.abstractIn this paper, we consider the estimation of a two parameters generalized Pareto mixture model(Hereinafter referred to as generalized Pareto mixture model) with density.The mixture model fits the real data very well. Due to the characteristics of thick tail, the Pareto distribution has been paid more and more attention in the field of financial risk measurement. At the same time, it has been wi...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=58248&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=60723
dc.subjectSCAD惩罚
dc.subject混合广义pareto分布
dc.subjectEM算法
dc.subjectSCAD penalty
dc.subjectGeneralized Pareto mixture model
dc.subjectEM algorithm
dc.titleSCAD惩罚混合广义Pareto模型的参数估计及应用
dc.title.alternativeParameter Estimation and Application of Generalized Pareto Mixtures via SCAD Penalty
dc.typethesis
dc.date.replied2017-05-26
dc.description.note学位:理学硕士
dc.description.note院系专业:数学科学学院_概率论与数理统计
dc.description.note学号:19020141152613


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