Comments on: model-based clustering and classification with non-normal mixture distributions

L. A. Garcia-Escudero; A. Gordaliza; A. Mayo-Iscar

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Comments on: model-based clustering and classification with non-normal mixture distributions

机译：评论：具有非正态混合分布的基于模型的聚类和分类

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First of all, we would like to congratulate S.X. Lee and G.J. McLachlan for this very stimulating work. The authors offer a motivating review of quite new approaches to deal with clustering and classification problems by resorting to mixtures of non-normal distributions. Apart from presenting a systematic classification of multivariate skew-distributions (see also, Lee and McLachlan 2013), they review other alternative asymmetric mixture models that have been recently considered in the literature. Moreover, five nice real data applications are shown which make clear that the use of non-normal mixtures can be very useful in different real data problems where normality of mixture components is clearly not satisfied. These examples nicely illustrate the increasing impact that non-normal mixture distributions will have in data modeling.

机译：首先，我们要祝贺S.X。李和G.J. McLachlan的这项令人振奋的工作。作者通过非正态分布的混合，对处理聚类和分类问题的相当新的方法进行了积极的回顾。除了提出多元偏态分布的系统分类（另请参见Lee和McLachlan 2013），他们还回顾了文献中最近考虑的其他替代性不对称混合模型。此外，显示了五个不错的真实数据应用程序，这些应用程序清楚地表明，在明显不满足混合物成分的正态性的不同实际数据问题中，使用非正态混合物可能非常有用。这些示例很好地说明了非正态混合分布将对数据建模产生越来越大的影响。

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《Statistical Methods and Applications》 |2013年第4期|459-461|共3页
作者
L. A. Garcia-Escudero; A. Gordaliza; A. Mayo-Iscar;
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IMUVA and Departamento de Estadistica e Investigacion Operativa, Facultad de Ciencias, Universidad de Valladolid, 47011 Valladolid, Spain;

IMUVA and Departamento de Estadistica e Investigacion Operativa, Facultad de Ciencias, Universidad de Valladolid, 47011 Valladolid, Spain;

IMUVA and Departamento de Estadistica e Investigacion Operativa, Facultad de Ciencias, Universidad de Valladolid, 47011 Valladolid, Spain;

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1. Comments on: model-based clustering and classification with non-normal mixture distributions [J] . L. A. García-Escudero, A. Gordaliza, A. Mayo-Iscar Statistical Methods & Applications . 2013,第4期

机译：评论：具有非正态混合分布的基于模型的聚类和分类
2. Discussion of ‘Model-based clustering and classification with non-normal mixture distributions’ by Lee and McLachlan [J] . Paul D. McNicholas, Ryan P. Browne, Paula M. Murray Statistical Methods & Applications . 2013,第4期

机译：Lee和McLachlan讨论了“具有非正态混合分布的基于模型的聚类和分类”
3. Discussion of “Model-based clustering and classification with non-normal mixture distributions” by S.X. Lee and G.J. McLachlan [J] . Giuliano Galimberti, Angela Montanari Statistical Methods & Applications . 2013,第4期

机译：S.X讨论了“基于模型的具有非正态混合分布的聚类和分类”。李和G.J.麦克拉克伦
4. Generative model-based speaker clustering via mixture of von Mises-Fisher distributions [C] . Hao Tang, Chu S.M., Huang T.S. IEEE International Conference on Acoustics, Speech and Signal Processing;ICASSP 2009 . 2009

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5. Latent Multi-State Models for Non-Equidistant Longitudinal Observations with Finite and Infinite Mixture Model-Based Clustering [D] . Luo, Yu. 2019

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6. Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions [O] . E Andres Houseman, Brock C Christensen, Ru-Fang Yeh, 2008

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7. Mixtures of Generalized Hyperbolic Distributions and Mixtures of Skew-t Distributions for Model-Based Clustering with Incomplete Data [O] . Wei, Yuhong, Tang, Yang, McNicholas, Paul D. 2017

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Comments on: model-based clustering and classification with non-normal mixture distributions

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