Model-based Clustering, Classification, And Density Estimation Using Mclust In R Av Luca Scrucca, Chris Fraley, T. Brendan Murphy, Adrian E. Raftery

<P><STRONG>Model-Based Clustering, Classification, and Denisty Estimation Using mclust in R</STRONG></P><P>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 <B>mclust</B> 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.</P><P><B>Key features of the book:</B></P><UL><LI>An introduction to the model-based approach and the <B>mclust</B> R package</LI><LI>A detailed description of <STRONG>mclust</STRONG> and the underlying modeling strategies</LI><LI>An extensive set of examples, color plots, and figures al

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