Model-Based Clustering and Classification for Data Science. With Applications in R, Hardback/Adrian E. Raftery

This accessible but rigorous introduction is written for advanced undergraduates and beginning graduate students in data science, as well as researchers and practitioners. It shows how a statistical framework yields sound estimation, testing and prediction methods, using extensive data examples and providing R code for many methods.