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Research Article

Model-based clustering via skewed matrix-variate cluster-weighted models

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Pages 2645-2666 | Received 04 Jan 2022, Accepted 26 May 2022, Published online: 23 Jun 2022

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Volodymyr Melnykov, Yang Wang, Yana Melnykov, Francesca Torti, Domenico Perrotta & Marco Riani. (2024) On Simulating Skewed and Cluster-Weighted Data for Studying Performance of Clustering Algorithms. Journal of Computational and Graphical Statistics 33:1, pages 303-309.
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Shaho Zarei. Cluster-weighted modeling with measurement error in covariates. Communications in Statistics - Theory and Methods 0:0, pages 1-13.
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Articles from other publishers (6)

Salvatore D. Tomarchio. (2022) Matrix-variate normal mean-variance Birnbaum–Saunders distributions and related mixture models. Computational Statistics 39:2, pages 405-432.
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Salvatore D. Tomarchio & Michael P. B. Gallaugher. (2024) Mixtures of regressions using matrix-variate heavy-tailed distributions. Advances in Data Analysis and Classification.
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Salvatore D. Tomarchio, Luca Bagnato & Antonio Punzo. (2023) Model-based clustering using a new multivariate skew distribution. Advances in Data Analysis and Classification 18:1, pages 61-83.
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Yasamin Ghahremani & Babak Amiri. (2024) Time Series Overlapping Clustering Based on Link Community Detection. IEEE Access 12, pages 41102-41124.
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Ryan P. Browne, Luca Bagnato & Antonio Punzo. (2023) Parsimony and parameter estimation for mixtures of multivariate leptokurtic-normal distributions. Advances in Data Analysis and Classification.
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Nikola Počuča, Michael P.B. Gallaugher, Katharine M. Clark & Paul D. McNicholas. (2023) Visual assessment of matrix‐variate normality. Australian & New Zealand Journal of Statistics 65:2, pages 152-165.
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