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A Mixture of Coalesced Generalized Hyperbolic Distributions

机译:聚结的广义双曲分布的混合物

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A mixture of multiple scaled generalized hyperbolic distributions (MMSGHDs) is introduced. Then, a coalesced generalized hyperbolic distribution (CGHD) is developed by joining a generalized hyperbolic distribution with a multiple scaled generalized hyperbolic distribution. After detailing the development of the MMSGHDs, which arises via implementation of a multi-dimensional weight function, the density of the mixture of CGHDs is developed. A parameter estimation scheme is developed using the ever-expanding class of MM algorithms and the Bayesian information criterion is used for model selection. The issue of cluster convexity is examined and a special case of the MMSGHDs is developed that is guaranteed to have convex clusters. These approaches are illustrated and compared using simulated and real data. The identifiability of the MMSGHDs and the mixture of CGHDs are discussed in an appendix.
机译:介绍了多个缩放的广义双曲分布(MMSGHDS)的混合物。 然后,通过将通用的双曲线分布加入多个缩放的广义双曲分布来开发聚结的广义双曲分布(CGHD)。 在详细解释通过实施多维重量函数的MMSGHDS的发展之后,开发了CGHDS的混合物的密度。 使用Eval-Adding的MM算法类和贝叶斯信息标准使用参数估计方案用于模型选择。 检查群集凸起的问题,并开发了一个特殊的MMSGHDS,保证具有凸粒簇。 使用模拟和实际数据进行说明和比较这些方法。 在附录中讨论了MMSGHDS和CGHD的混合物的可识别性。

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