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 methods 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.
Key features of the book:
An introduction to the model-based approach and the mclust R packageA detailed description of mclust and the underlying modeling strategiesAn extensive set of examples, color Descriptions and figures along with the R code for reproducing themSupported by a

https://mclust-org.github.io/book/

, including the R code to reproduce the examples and figures presented in the book, errata, and other supplementary material
The book is accessible to quantitatively trained students and researchers with a basic understanding of statistical methods, including inference and computing. In addition to serving as a reference manual for mclust , the book will be particularly useful to those wishing to employ these model-based techniques in research or applications in statistics, data science, clinical research, social science, and many other disciplines.


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