Random Partition Models for Microclustering Tasks
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2020/12/08
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Indian UGC (journal)
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Refrences46
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Citations13
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Brenda Betancourt Department of Statistics, University of Florida, Gainesville, FL;
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Giacomo Zanella Department of Decision Sciences, Bocconi University, BIDSA and IGIER, Milan, Italy; ORCID (unauthenticated)
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Rebecca C. Steorts Department of Statistical Science and Computer Science, Duke University, Durham, NC
Cite
Betancourt, Brenda, et al. “Random Partition Models for Microclustering Tasks”. Journal of the American Statistical Association, vol. 117, no. 539, 2020, pp. 1215-27, https://doi.org/10.1080/01621459.2020.1841647.
Betancourt, B., Zanella, G., & Steorts, R. C. (2020). Random Partition Models for Microclustering Tasks. Journal of the American Statistical Association, 117(539), 1215-1227. https://doi.org/10.1080/01621459.2020.1841647
Betancourt, Brenda, Giacomo Zanella, and Rebecca C. Steorts. “Random Partition Models for Microclustering Tasks”. Journal of the American Statistical Association 117, no. 539 (2020): 1215-27. https://doi.org/10.1080/01621459.2020.1841647.
Betancourt B, Zanella G, Steorts RC. Random Partition Models for Microclustering Tasks. Journal of the American Statistical Association. 2020;117(539):1215-27.
Journal Categories
Science
Mathematics
Science
Mathematics
Probabilities
Mathematical statistics
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
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| Title | 2017 | |||
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| Title | 1994 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Fast generation of exchangeable sequences of clusters data | Statistics and Computing |
| 2024 | |
| Bayesian estimation of cluster covariance matrices of unknown form | Journal of Econometrics |
| 2024 | |
Convergence Diagnostics for Entity Resolution | Annual Review of Statistics and Its Application |
| 2024 | |
A Bayesian record linkage model incorporating relational data | Applied Stochastic Models in Business and Industry |
| 2023 | |
Entropy regularization in probabilistic clustering | Statistical Methods & Applications |
| 2023 |
Citations Analysis
The category
Science: Mathematics: Probabilities. Mathematical statistics 10
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled d-blink: Distributed End-to-End Bayesian Entity Resolution and was published in 2021. The most recent citation comes from a 2024 study titled Convergence Diagnostics for Entity Resolution. This article reached its peak citation in 2023, with 6 citations. It has been cited in 12 different journals. Among related journals, the Journal of the American Statistical Association cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.