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

15 in stock


    View other formats and editions of Graphical Models in Applied Multivariate by J. Whittaker

    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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