Vine copula mixture models and clustering for non-Gaussian data
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[1] Ling Hu. Dependence patterns across financial markets: a mixed copula approach , 2006 .
[2] Gérard Govaert,et al. Assessing a Mixture Model for Clustering with the Integrated Completed Likelihood , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[3] T. Bedford,et al. Vines: A new graphical model for dependent random variables , 2002 .
[4] Mathieu Vrac,et al. Mixture decomposition of distributions by copulas in the symbolic data analysis framework , 2005, Discret. Appl. Math..
[5] K. Sachs,et al. Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data , 2005, Science.
[6] Jong-Min Kim,et al. Mixture of D-vine copulas for modeling dependence , 2013, Comput. Stat. Data Anal..
[7] Luca Scrucca,et al. mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models , 2016, R J..
[8] H. Akaike,et al. Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .
[9] Ryan P. Browne,et al. Mixtures of Shifted AsymmetricLaplace Distributions , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] Roger M. Cooke,et al. Probability Density Decomposition for Conditionally Dependent Random Variables Modeled by Vines , 2001, Annals of Mathematics and Artificial Intelligence.
[11] Ryan P. Browne,et al. A mixture of SDB skew-t factor analyzers , 2013, 1310.6224.
[12] E. Diday,et al. Clustering a Global Field of Atmospheric Profiles by Mixture Decomposition of Copulas , 2005 .
[13] Claudia Czado,et al. Model selection in sparse high-dimensional vine copula models with an application to portfolio risk , 2019, J. Multivar. Anal..
[14] Claudia Czado,et al. Selecting and estimating regular vine copulae and application to financial returns , 2012, Comput. Stat. Data Anal..
[15] Goran Strbac,et al. C-Vine Copula Mixture Model for Clustering of Residential Electrical Load Pattern Data , 2017, IEEE Transactions on Power Systems.
[16] P. McNicholas,et al. Outlier Detection via Parsimonious Mixtures of Contaminated Gaussian Distributions , 2013 .
[17] V. H. Lachos,et al. mixsmsn: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions , 2013 .
[18] M. Delignette-Muller,et al. fitdistrplus: An R Package for Fitting Distributions , 2015 .
[19] Paul D. McNicholas,et al. Model-Based Clustering , 2016, Journal of Classification.
[20] Gregor N. F. Weiß,et al. Mixture Pair-Copula-Constructions , 2015 .
[21] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[22] C. Czado,et al. Truncated regular vines in high dimensions with application to financial data , 2012 .
[23] Victor H. Lachos,et al. Multivariate mixture modeling using skew-normal independent distributions , 2012, Comput. Stat. Data Anal..
[24] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[25] Geoffrey J. McLachlan,et al. Robust mixture modelling using the t distribution , 2000, Stat. Comput..
[26] Marc S. Paolella,et al. Robust normal mixtures for financial portfolio allocation , 2017 .
[27] Dimitris Karlis,et al. Model-based clustering using copulas with applications , 2014, Statistics and Computing.
[28] Claudia Czado,et al. Pair Copula Constructions for Multivariate Discrete Data , 2012 .
[29] Ryan P. Browne,et al. A mixture of generalized hyperbolic distributions , 2013, 1305.1036.
[30] Grace Y. Yi,et al. A bayesian nonparametric mixture model for grouping dependence structures and selecting copula functions , 2021 .
[31] M. Sklar. Fonctions de repartition a n dimensions et leurs marges , 1959 .
[32] G. Celeux,et al. Variable Selection for Clustering with Gaussian Mixture Models , 2009, Biometrics.
[33] Geoffrey J. McLachlan,et al. Finite mixtures of multivariate skew t-distributions: some recent and new results , 2014, Stat. Comput..
[34] Claudia Czado,et al. Model selection for discrete regular vine copulas , 2017, Comput. Stat. Data Anal..
[35] Adrian E. Raftery,et al. Improved initialisation of model-based clustering using Gaussian hierarchical partitions , 2015, Adv. Data Anal. Classif..
[36] H. Joe. Families of $m$-variate distributions with given margins and $m(m-1)/2$ bivariate dependence parameters , 1996 .
[37] Dimitris Karlis,et al. Choosing Initial Values for the EM Algorithm for Finite Mixtures , 2003, Comput. Stat. Data Anal..
[38] A. Frigessi,et al. Pair-copula constructions of multiple dependence , 2009 .
[39] Xiao-Li Meng,et al. Maximum likelihood estimation via the ECM algorithm: A general framework , 1993 .
[40] A. Raftery,et al. Variable Selection for Model-Based Clustering , 2006 .
[41] Wan-Lun Wang,et al. Robust model-based clustering via mixtures of skew-t distributions with missing information , 2015, Advances in Data Analysis and Classification.
[42] Qingyang Zhang,et al. A mixture copula Bayesian network model for multimodal genomic data , 2017, bioRxiv.
[43] Charles Bouveyron,et al. Model-based clustering of high-dimensional data: A review , 2014, Comput. Stat. Data Anal..
[44] P. McNicholas,et al. Mixtures of modified t-factor analyzers for model-based clustering, classification, and discriminant , 2011 .
[45] Claudia Czado,et al. Analyzing Dependent Data with Vine Copulas , 2019, Lecture Notes in Statistics.
[46] Claudia Czado,et al. Simplified pair copula constructions - Limitations and extensions , 2013, J. Multivar. Anal..
[47] H. Joe,et al. The Estimation Method of Inference Functions for Margins for Multivariate Models , 1996 .
[48] Anandarup Roy,et al. Pair-copula based mixture models and their application in clustering , 2014, Pattern Recognit..
[49] P. Embrechts,et al. Dependence modeling with copulas , 2007 .
[50] William Nick Street,et al. Breast Cancer Diagnosis and Prognosis Via Linear Programming , 1995, Oper. Res..
[51] Ryan P. Browne,et al. Mixtures of multivariate power exponential distributions , 2015, Biometrics.
[52] D. Rubin,et al. The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence , 1994 .
[53] Gérard Govaert,et al. Gaussian parsimonious clustering models , 1995, Pattern Recognit..
[54] BiernackiChristophe,et al. Assessing a Mixture Model for Clustering with the Integrated Completed Likelihood , 2000 .
[55] Pavel Krupskii,et al. Factor copula models for multivariate data , 2013, J. Multivar. Anal..
[56] Tsung-I Lin,et al. Finite mixture modelling using the skew normal distribution , 2007 .
[57] Adrian E. Raftery,et al. How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis , 1998, Comput. J..
[58] Christian Hennig,et al. Methods for merging Gaussian mixture components , 2010, Adv. Data Anal. Classif..
[59] Jacques Janssen,et al. Clayton copula and mixture decomposition , 2005 .