Hierarchical variable clustering via copula-based divergence measures between random vectors
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2024/02/01
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Indian UGC (journal)
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Refrences41
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Citations1
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Steven De Keyser
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Irène Gijbels ORCID (unauthenticated)
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Technology
Mechanical engineering and machinery
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| A new class of symmetric distributions including the elliptically symmetric logistic | Communications in Statistics - Theory and Methods |
| 2 | 2022 |
Dissimilarity measure for ranking data via mixture of copulae* | Statistical Analysis and Data Mining: The ASA Data Science Journal |
| 8 | 2019 |
| Probit transformation for nonparametric kernel estimation of the copula density | Bernoulli |
| 2017 | |
| Adaptive estimation of the copula correlation matrix for semiparametric elliptical copulas | Bernoulli |
| 2016 | |
Shannon Entropy and Mutual Information for Multivariate Skew‐Elliptical Distributions | Scandinavian Journal of Statistics |
| 56 | 2013 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Hierarchical variable clustering via copula-based divergence measures between random vectors | International Journal of Approximate Reasoning |
| 1 | 2024 |
Citations Analysis
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 1
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Hierarchical variable clustering via copula-based divergence measures between random vectors and was published in 2024. The most recent citation comes from a 2024 study titled Hierarchical variable clustering via copula-based divergence measures between random vectors. This article reached its peak citation in 2024, with 1 citations. It has been cited in 1 different journals. Among related journals, the International Journal of Approximate Reasoning cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.