Graphical models in applied multivariate statistics
著者
書誌事項
Graphical models in applied multivariate statistics
（Wiley series in probability and mathematical statistics, . Probability and mathematical statistics）
John Wiley & Sons, c1990
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注記
Bibliography: p. 426-435
Includes indexes
内容説明・目次
内容説明
Graphical models--a subset of log-linear models--reveal the interrelationships between multiple variables and features of the underlying conditional independence. Following the theorem-proof-remarks format, this introduction to the use of graphical models in the description and modeling of multivariate systems 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.
目次
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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