Model-Based Clustering, Classification, and Density Estimation Using mclust in R (Chapman & Hall/CRC The R Series) 1st Edition
by Luca Scrucca (Author), Chris Fraley (Author), T. Brendan Murphy (Author), Raftery Adrian E. (Author)
Publisher Finelybook 出版社：Chapman and Hall/CRC; 1st edition (June 8, 2023)
pages 页数：288 pages
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 package
A detailed description of mclust and the underlying modeling strategies
An extensive set of examples, color plots and figures along with the R code for reproducing them
Supported by a companion website, 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.