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Journal of Applied Statistics Volume 45, 2018 - Issue 2
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Original Articles

A new algorithm for clustering based on kernel density estimation

L. C. MatioliDep. de Matemática, Universidade Federal do Paraná-UFPR, Curitiba, BrazilCorrespondence[email protected]
ORCID Iconhttp://orcid.org/0000-0002-6506-3550
ORCID Icon,
S.R. SantosDep. de Mat., Universidade Estadual do Paraná-UNESPAR, Campo Mourão, Brazil
,
M. KleinaDep. de Engenharia de Produção, Universidade Federal do Paraná-UFPR, Curitiba, Brazil;Sistema Metereológico do Paraná-SIMEPAR, Curitiba, Brazil
&
E. A. LeiteSistema Metereológico do Paraná-SIMEPAR, Curitiba, Brazil
Pages 347-366 | Received 09 Jul 2015, Accepted 20 Dec 2016, Published online: 12 Jan 2017

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D. Scaldelai, L. C. Matioli & S. R. Santos. (2024) TreeKDE: clustering multivariate data based on decision tree and using one-dimensional kernel density estimation. Journal of Applied Statistics 51:4, pages 740-758.
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Soumita Modak. (2023) A new measure for assessment of clustering based on kernel density estimation. Communications in Statistics - Theory and Methods 52:17, pages 5942-5951.
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Soumita Modak. (2023) Pointwise norm-based clustering of data in arbitrary dimensional space. Communications in Statistics: Case Studies, Data Analysis and Applications 9:2, pages 121-134.
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Soumita Modak. (2023) A new interpoint distance-based clustering algorithm using kernel density estimation. Communications in Statistics - Simulation and Computation 0:0, pages 1-19.
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Soumita Modak. (2022) A new nonparametric interpoint distance-based measure for assessment of clustering. Journal of Statistical Computation and Simulation 92:5, pages 1062-1077.
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D. Scaldelai, L. C. Matioli, S. R. Santos & M. Kleina. (2022) MulticlusterKDE: a new algorithm for clustering based on multivariate kernel density estimation. Journal of Applied Statistics 49:1, pages 98-121.
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Jie Chen. (2021) Editorial. Journal of Applied Statistics 48:1, pages 1-3.
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Soumita Modak. Determination of the number of clusters through logistic regression analysis. Journal of Applied Statistics 0:0, pages 1-20.
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