Tutorial: A Greedy and Optimistic Approach to Clustering: Applications in Astronomy
##article.authors##
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Akifumi Okuno
Institute of Statistical Mathematics, Department of Fundamental Statistical Mathematics
https://researchmap.jp/aokuno
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Kohei Hattori
National Astronomical Observatory of Japan, Research Enhancement Strategy Office
https://researchmap.jp/Kohei_Hattori_Gaia
DOI:
https://doi.org/10.51094/jxiv.1290Keywords:
Clustering, Uncertainty, OptimisticAbstract
本稿は The Astrophysical Journal および Annals of the Institute of Statistical Mathematics に採択された我々の原著論文: Hattori et al. (2023) と Okuno and Hattori (2025) に関する解説です．解説の平易さを優先するため，より厳密な記述については原著論文をご参照ください．
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References
Hattori, K., Okuno, A., and Roederer, I. U. (2023). Finding r-II sibling stars in the milky way with the greedy optimistic clustering algorithm. The Astrophysical Journal, 946(1):48.
Okuno, A. and Hattori, K. (2025). A greedy and optimistic clustering for leveraging individual covariate uncertainty. Annals of the Institute of Statistical Mathematics. accepted.
Roederer, I. U., Hattori, K., and Valluri, M. (2018). Kinematics of highly r-process-enhanced field stars: Evidence for an accretion origin and detection of several groups from disrupted satellites. The Astronomical Journal, 156(4):179.
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Submitted: 2025-06-03 08:53:01 UTC
Published: 2025-06-05 10:17:10 UTC
License
Copyright (c) 2025
Akifumi Okuno
Kohei Hattori
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
