In this book, the authors give a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions. This area of statistics is important to a range of disciplines, and it's methodology is attracting interest from researchers in the fields in which it can be applied. Applications include sedimentology, fisheries research, medicine, remote sensing and economics. More indirect applications include outlier models, density estimation, Bayesian and empirical Bayes analysis and robustness studies. All these areas of application are discussed in detail, before the related mathematical concepts are introduced. Concepts discussed include identifiability and information, and there is a substantial account of the inferential problems associated with using data from a mixture. A particularly awkward problem tackled here is that of deciding how many components the underlying mixture contains. Because of estimation difficulties, and to cope with applications in engineering, the authors have developed approximate sequential methods, these are described in the final chapter.

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