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Graphical Models with R

Søren Højsgaard
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      Graphical models in their modern form have been around since the late 1970s and appear today in many areas of the sciences.  Along with the ongoing developments of graphical models, a number of different graphical modeling software programs have been written over the years.  In recent years many of these software developments have taken place within the R community, either in the form of new packages or by providing an R interface to existing software.  This book attempts to give the reader a gentle introduction to graphical modeling using R and the main features of some of these packages.  In addition, the book provides examples of how more advanced aspects of graphical modeling can be represented and handled within R.  Topics covered in the seven chapters include graphical models for contingency tables, Gaussian and mixed graphical models, Bayesian networks and modeling high dimensional data.
      Format: Paperback / softback CONTRIBUTORS: Søren Højsgaard EAN: 9781461422983 COUNTRY: United States PAGES: WEIGHT: 302 g HEIGHT: 235 cm
      PUBLISHED BY: Springer-Verlag New York Inc. DATE PUBLISHED: 2012-02-18 CITY: GENRE: MATHEMATICS / Probability & Statistics / General WIDTH: 155 cm SPINE:

      Book Themes:

      Probability and statistics

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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 in their modern form have been around since the late 1970s and appear today in many areas of the sciences.  Along with the ongoing developments of graphical models, a number of different graphical modeling software programs have been written over the years.  In recent years many of these software developments have taken place within the R community, either in the form of new packages or by providing an R interface to existing software.  This book attempts to give the reader a gentle introduction to graphical modeling using R and the main features of some of these packages.  In addition, the book provides examples of how more advanced aspects of graphical modeling can be represented and handled within R.  Topics covered in the seven chapters include graphical models for contingency tables, Gaussian and mixed graphical models, Bayesian networks and modeling high dimensional data.
      Format: Paperback / softback CONTRIBUTORS: Søren Højsgaard EAN: 9781461422983 COUNTRY: United States PAGES: WEIGHT: 302 g HEIGHT: 235 cm
      PUBLISHED BY: Springer-Verlag New York Inc. DATE PUBLISHED: 2012-02-18 CITY: GENRE: MATHEMATICS / Probability & Statistics / General WIDTH: 155 cm SPINE:

      Book Themes:

      Probability and statistics

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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.

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