publishing Jacques and Murphy

Author: jchiquet

_bibliography/in_production.bib

@@ -1,26 +1 @@
 
-@article{jacques2025,
-  bibtex_show = {true},
-  author = {Jacques, Julien and Brendan Murphy, Thomas},
-  publisher = {French Statistical Society},
-  title = {Model-Based {Clustering} and {Variable} {Selection} for
-    {Multivariate} {Count} {Data}},
-  journal = {Computo},
-  date = {2025-07-01},
-  doi = {10.57750/6v7b-8483},
-  issn = {2824-7795},
-  langid = {en},
-  abstract = {Model-based clustering provides a principled way of
-    developing clustering methods. We develop a new model-based
-    clustering methods for count data. The method combines clustering
-    and variable selection for improved clustering. The method is based
-    on conditionally independent Poisson mixture models and Poisson
-    generalized linear models. The method is demonstrated on simulated
-    data and data from an ultra running race, where the method yields
-    excellent clustering and variable selection performance.},
-  year    = 2025,
-  type        = {{Research article}},
-  domain      = {Statistics},
-  language    = {R},
-  repository  = {published-202507-jacques-count-data},
-}

_bibliography/published.bib

@@ -1,3 +1,29 @@
+@article{jacques2025,
+  bibtex_show = {true},
+  author = {Jacques, Julien and Brendan Murphy, Thomas},
+  publisher = {French Statistical Society},
+  title = {Model-Based {Clustering} and {Variable} {Selection} for
+    {Multivariate} {Count} {Data}},
+  journal = {Computo},
+  date = {2025-07-01},
+  doi = {10.57750/6v7b-8483},
+  issn = {2824-7795},
+  langid = {en},
+  abstract = {Model-based clustering provides a principled way of
+    developing clustering methods. We develop a new model-based
+    clustering methods for count data. The method combines clustering
+    and variable selection for improved clustering. The method is based
+    on conditionally independent Poisson mixture models and Poisson
+    generalized linear models. The method is demonstrated on simulated
+    data and data from an ultra running race, where the method yields
+    excellent clustering and variable selection performance.},
+  year    = 2025,
+  type        = {{Research article}},
+  domain      = {Statistics},
+  language    = {R},
+  repository  = {published-202507-jacques-count-data},
+}
+
 @article{ferte2025,
   bibtex_show = {true},
   author = {Ferté, Thomas and Ba, Kalidou and Dutartre, Dan and Legrand,

_news/announcement_publication_202507.md

@@ -0,0 +1,8 @@
+---
+layout: post
+date: 2025-07-01 07:59:00-0400
+inline: true
+---
+
+A new article was published, by
+   Julien Jacques and Thomas Brendan Murphy: [Model-Based Clustering and Variable Selection for Multivariate Count Data](https://computo-journal.org/published-202507-jacques-count-data/)