A copula-based algorithm for discovering patterns of dependent observations

DOI10.1007/S00357-012-9099-YzbMath1360.62250DBLPjournals/classification/LascioG12OpenAlexW1976624196WikidataQ59426189 ScholiaQ59426189MaRDI QIDQ263332

F. Marta L. Di Lascio, Simone Giannerini

Publication date: 4 April 2016

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00357-012-9099-y

zbMATH Keywords

model-based clusteringclustering methodsCoClust algorithmcopula functionsmicroarray data

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (6)

Clustering Microarray Data: Theoretical and Practical Issues ⋮ Model-based clustering ⋮ Model-based clustering using copulas with applications ⋮ Clustering dependent observations with copula functions ⋮ Hierarchical time series clustering on tail dependence with linkage based on a multivariate copula approach ⋮ Mixtures of Gaussian copula factor analyzers for clustering high dimensional data

Uses Software

• CoClust

Cites Work

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• An introduction to copulas.
• Hybrid hierarchical clustering with applications to microarray data
• How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis
• Statistical Applications of the Multivariate Skew Normal Distribution
• The multivariate skew-normal distribution
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• An Optimum Property of Regular Maximum Likelihood Estimation

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