Hierarchical variable clustering based on the predictive strength between random vectors
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Publication:6577621
DOI10.1016/j.ijar.2024.109185MaRDI QIDQ6577621
Publication date: 24 July 2024
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
dissimilaritydirected dependence(mutual) perfect dependenceagglomerative hierarchical variable clustering
Cites Work
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- A simple measure of conditional dependence
- A new coefficient of correlation
- An introduction to copulas.
- Dissimilarity functions for rank-invariant hierarchical clustering of continuous variables
- On conditional weak convergence
- Agglomerative hierarchical clustering of continuous variables based on mutual information
- Supervised feature selection by clustering using conditional mutual information-based distances
- Multivariate comonotonicity
- On the theory of elliptically contoured distributions
- Cluster analysis and mathematical programming
- The concept of comonotonicity in actuarial science and finance: theory.
- Extremal dependence concepts
- Clustering of financial time series in risky scenarios
- Cluster Analysis
- A Method for Comparing Two Hierarchical Clusterings
- Finding Groups in Data
- Copulas and Dependence Models with Applications
- Principles of Copula Theory
- Correlation and Complete Dependence of Random Variables
- On Information and Sufficiency
- Hierarchical variable clustering via copula-based divergence measures between random vectors
- Quantifying directed dependence via dimension reduction
- Nonparametric estimation of the multivariate Spearman's footrule: a further discussion
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