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.
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Søren Højsgaard is Associate Professor in Statistics and Head of the Department of Mathematical Sciences at Aalborg University. David Edwards is Associate Professor at the Department of Molecular Biology and Genetics, Aarhus University. Steffen Lauritzen is Professor of Statistics and Head of the Department of Statistics at the University of Oxford.
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.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 do. Nº de ref. del artículo: 4189430
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