Description

Book Synopsis
- It reveals the interrelationships between multiple variables and features of the underlying conditional independence. - It covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. - Many numerical examples and exercises with solutions are included.

Table of Contents
Independence and Interaction.

Independence Graphs.

Information Divergence.

The Inverse Variance.

Graphical Gaussian Models.

Graphical Log-Linear Models.

Model Selection.

Methods for Sparse Tables.

Regression and Graphical Chain Models.

Models for Mixed Variables.

Decompositions and Decomposability.

Appendices.

References.

Author Index.

Subject Index.

Graphical Models in Applied Multivariate

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    A Paperback / softback by J. Whittaker

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      Publisher: John Wiley & Sons Inc
      Publication Date: 28/10/2008
      ISBN13: 9780470743669, 978-0470743669
      ISBN10: 0470743662
      Also in:
      Mathematics Mathematical modelling Probability and statistics

      Description

      Book Synopsis
      - It reveals the interrelationships between multiple variables and features of the underlying conditional independence. - It covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. - Many numerical examples and exercises with solutions are included.

      Table of Contents
      Independence and Interaction.

      Independence Graphs.

      Information Divergence.

      The Inverse Variance.

      Graphical Gaussian Models.

      Graphical Log-Linear Models.

      Model Selection.

      Methods for Sparse Tables.

      Regression and Graphical Chain Models.

      Models for Mixed Variables.

      Decompositions and Decomposability.

      Appendices.

      References.

      Author Index.

      Subject Index.

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