T. Brendan Murphy : Model-Based Clustering, Classification, and Density Estimation Using mclust in R

Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing an appropriate clustering or classification method to be understood within the context of statistical modeling. The mclust package for the statistical environment R is a widely adopted platform implementing these model-based strategies. The package includes both summary and visual functionality, complementing procedures for estimating and choosing models.

Book available : Routledge/Taylor and Francis Group

• Editor
  Chapman and Hall/CRC
• Author(s)

  Brendan Murphy is Full Professor of Statistics in the School of Mathematics and Statistics at University College Dublin. His research interests include clustering, classification and latent variable modelling, particularly he is interested in applications from social sciences, food science, medicine and biology.
  He was a 2021-2022 Fellow at the Collegium of Lyon.
  
  Luca Scrucca is Associate Professor of Statistics at Università degli Studi di Perugia
  
  Chris Fraley is a researcher in statistics at the University of Washington.

  Adrian Raftery is Professor Emeritus of Statistics and Sociology at the University of Washington.