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Handbook of mixed membership models and their applications

Contributor(s): Airoldi, Edoardo M [Editor] | Blei, David M [Editor] | Erosheva, Elena A [Editor] | Fienberg, Stephen E [Editor].
Series: Chapman &​ Hall/​CRC handbooks of modern statistical methods. Publisher: Boca Raton CRC Press 2015Description: xxxiii, 585 p.ISBN: 9781466504080.Subject(s): Analysis of variance | Mathematical statistics | Multivariate Data | ClusteranalyseDDC classification: 519.5 Summary: In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, you’ll discover how to characterize complex multivariate data in: • Studies involving genetic databases • Patterns in the progression of diseases and disabilities • Combinations of topics covered by text documents • Political ideology or electorate voting patterns • Heterogeneous relationships in networks, and much more The handbook spans more than 20 years of the editors’ and contributors’ statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models. (https://www.crcpress.com/Handbook-of-Mixed-Membership-Models-and-Their-Applications/Airoldi-Blei-Erosheva-Fienberg/9781466504080)
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Table of contents:

I. Mixed membership: setting the stage
II. The grade of membership model and its extensions
III. Topic models: mixed membership models for text
IV. Semi-supervised mixed membership models
V. Special methodology for sequence and rank data
VI. Mixed membership models for networks.

In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology.
Through examples using real data sets, you’ll discover how to characterize complex multivariate data in:
• Studies involving genetic databases
• Patterns in the progression of diseases and disabilities
• Combinations of topics covered by text documents
• Political ideology or electorate voting patterns
• Heterogeneous relationships in networks, and much more
The handbook spans more than 20 years of the editors’ and contributors’ statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models.

(https://www.crcpress.com/Handbook-of-Mixed-Membership-Models-and-Their-Applications/Airoldi-Blei-Erosheva-Fienberg/9781466504080)

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