Browsing by Subject "cluster analysis"

Now showing items 1-3 of 3

    • The Adaptive, Pain Sensitive, and Global Symptoms Clusters: Evidence from a Patient-Based Study 

      Al-Hamed, F. S.; Alonso, A. A.; Vivaldi, D.; Smith, S. B.; Meloto, C. B. ( SAGE , 2023 , Article)
      Objectives: The largest epidemiologic study conducted about painful temporomandibular disorders (pTMDs) to date identified 3 clusters of individuals with similar symptoms—adaptive, pain sensitive, and global symptoms—which ...

    • Bayesian Hierarchical Clustering for Studying Cancer Gene Expression Data with Unknown Statistics 

      Sirinukunwattana, Korsuk; Savage, Richard S.; Bari, Muhammad F.; Snead, David R.J.; Rajpoot, Nasir M. ( Public Library of Science , 2013 , Article)
      Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve ...

    • Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome 

      Thomas, H. J. D.; Myers-Smith, I. H.; Bjorkman, A. D.; Elmendorf, S. C.; Blok, D.; ... more authors ( Wiley , 2019 , Article)
      Aim: Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional ...