Graphical models are of great interest in statistics and computer science. This book is more oriented towards applications than other books on this subject, and it will be of interest to researchers and graduate students in both of these areas.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
A useful introduction to this topic for both students and researchers, with an emphasis on applications and practicalities rather than on a formal development. It is based on the popular software package for graphical modelling, MIM, freely available for downloading from the Internet. Following a description of some of the basic ideas of graphical modelling, subsequent chapters describe particular families of models, including log-linear models, Gaussian models, and models for mixed discrete and continuous variables. Further chapters cover hypothesis testing and model selection. Chapters 7 and 8 are new to this second edition and describe the use of directed, chain, and other graphs, complete with a summary of recent work on causal inference.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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