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+ @article {jacques2025 ,
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+ bibtex_show = { true} ,
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+ author = { Jacques, Julien and Brendan Murphy, Thomas} ,
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+ publisher = { French Statistical Society} ,
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+ title = { Model-Based {Clustering} and {Variable} {Selection} for
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+ {Multivariate} {Count} {Data}} ,
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+ journal = { Computo} ,
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+ date = { 2025-07-01} ,
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+ doi = { 10.57750/6v7b-8483} ,
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+ issn = { 2824-7795} ,
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+ langid = { en} ,
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+ abstract = { Model-based clustering provides a principled way of
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+ developing clustering methods. We develop a new model-based
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+ clustering methods for count data. The method combines clustering
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+ and variable selection for improved clustering. The method is based
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+ on conditionally independent Poisson mixture models and Poisson
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+ generalized linear models. The method is demonstrated on simulated
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+ data and data from an ultra running race, where the method yields
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+ excellent clustering and variable selection performance.}
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+ year = 2025 ,
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+ type = { {Research article}} ,
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+ domain = { Statistics} ,
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+ language = { R} ,
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+ repository = { published-202507-jacques-count-data} ,
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+ }
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