| Description |
1 online resource (251 pages) |
| Contents |
Cover; Half Title; Title; Copyright; Dedication; Table of Contents; List of Figures; List of Tables; Preface; 1 Introduction; 1.1 Classification; 1.2 Finite Mixture Models; 1.3 Model-Based Clustering, Classification, and Discriminant Analysis; 1.4 Comparing Partitions; 1.5 R Packages; 1.6 Datasets; 1.7 Outline of the Contents of This Monograph; 2 Mixtures of Multivariate Gaussian Distributions; 2.1 Historical Development; 2.2 Parameter Estimation; 2.2.1 Model-Based Clustering; 2.2.2 Model-Based Classification; 2.2.3 Model-Based Discriminant Analysis |
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2.2.4 Initialization via Deterministic Annealing2.2.5 Stopping Rules; 2.3 Gaussian Parsimonious Clustering Models; 2.4 Model Selection; 2.5 Merging Gaussian Components; 2.6 Illustrations; 2.6.1 x2 Data; 2.6.2 Banknote Data; 2.6.3 Female Voles Data; 2.6.4 Italian Olive Oil Data; 2.7 Comments; 3 Mixtures of Factor Analyzers and Extensions; 3.1 Factor Analysis; 3.1.1 The Model; 3.1.2 An EM Algorithm for the Factor Analysis Model; 3.1.3 Woodbury Identity; 3.1.4 Comments; 3.2 Mixture of Factor Analyzers; 3.3 Parsimonious Gaussian Mixture Models; 3.3.1 A Family of Eight Models |
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3.3.2 Parameter Estimation3.3.3 Comments; 3.4 Expanded Parsimonious Gaussian Mixture Models; 3.4.1 A Family of Twelve Models; 3.4.2 Parameter Estimation; 3.5 Mixture of Common Factor Analyzers; 3.5.1 The Model; 3.5.2 Parameter Estimation; 3.5.3 Discussion; 3.6 Illustrations; 3.6.1 x2 Data; 3.6.2 Italian Wine Data; 3.6.3 Italian Olive Oil Data; 3.6.4 Alon Colon Cancer Data; 3.7 Comments; 4 Dimension Reduction and High-Dimensional Data; 4.1 Implicit and Explicit Approaches; 4.2 PGMM Family in High-Dimensional Applications; 4.3 VSCC; 4.4 clustvarsel and selvarclust; 4.5 GMMDR; 4.6 HD-GMM |
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4.7 Illustrations4.7.1 Coffee Data; 4.7.2 Leptograpsus Crabs; 4.7.3 Banknote Data; 4.7.4 Wisconsin Breast Cancer Data; 4.7.5 Leukaemia Data; 4.8 Comments; 5 Mixtures of Distributions with Varying Tail Weight; 5.1 Mixtures of Multivariate t-Distributions; 5.2 Mixtures of Power Exponential Distributions; 5.3 Illustrations; 5.3.1 Overview; 5.3.2 x2 Data; 5.3.3 Body Data; 5.3.4 Diabetes Data; 5.3.5 Female Voles Data; 5.3.6 Leptograpsus Crabs Data; 5.4 Comments; 6 Mixtures of Generalized Hyperbolic Distributions; 6.1 Overview; 6.2 Generalized Inverse Gaussian Distribution; 6.2.1 A Parameterization |
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6.2.2 An Alternative Parameterization6.3 Mixtures of Shifted Asymmetric Laplace Distributions; 6.3.1 Shifted Asymmetric Laplace Distribution; 6.3.2 Parameter Estimation; 6.3.3 SAL Mixtures versus Gaussian Mixtures; 6.4 Mixture of Generalized Hyperbolic Distributions; 6.4.1 Generalized Hyperbolic Distribution; 6.4.2 Parameter Estimation; 6.5 Mixture of Generalized Hyperbolic Factor Analyzers; 6.5.1 The Model; 6.5.2 Parameter Estimation; 6.5.3 Analogy with the Gaussian Solution; 6.6 Illustrations; 6.6.1 Old Faithful Data; 6.6.2 Yeast Data; 6.6.3 Italian Wine Data; 6.6.4 Liver Data |
| Notes |
6.7 A Note on Normal Variance-Mean Mixtures |
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Print version record |
| Subject |
Multiple comparisons (Statistics)
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Classification -- Methods -- Mathematics
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Discriminant analysis.
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Mixture distributions (Probability theory)
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Hierarchical clustering (Cluster analysis)
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Discriminant analysis
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Hierarchical clustering (Cluster analysis)
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Mixture distributions (Probability theory)
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Multiple comparisons (Statistics)
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| Form |
Electronic book
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| ISBN |
9781315356112 |
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1315356112 |
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9781315337050 |
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1315337053 |
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9781482225679 |
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1482225670 |
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9781315373577 |
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1315373572 |
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