Handbook of Mixed Membership Models and Their Applications
Crc Press Inc (Verlag)
978-1-4665-0408-0 (ISBN)
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.
Edoardo M. Airoldi is an associate professor of statistics at Harvard University. Dr. Airoldi’s current research focuses on statistical theory and methods for designing and analyzing experiments in the presence of network interference as well as on modeling and inferential issues when dealing with network data. David M. Blei is a professor of statistics and computer science at Columbia University. Dr. Blei’s research is in statistical machine learning involving probabilistic topic models, Bayesian nonparametric methods, and approximate posterior inference. Elena A. Erosheva is an associate professor of statistics and social work at the University of Washington, where she is a core member of the Center for Statistics and the Social Sciences. Dr. Erosheva’s research focuses on the development and application of modern statistical methods to address important issues in the social, medical, and health sciences. Stephen E. Fienberg is the Maurice Falk University Professor of Statistics and Social Science at Carnegie Mellon University, where he is co-director of the Living Analytics Research Centre and a member of the Department of Statistics, the Machine Learning Department, the Heinz College, and Cylab. Dr. Fienberg’s research includes the development of statistical methods for categorical data analysis and network data analysis.
Mixed Membership: Setting the Stage. The Grade of Membership Model and Its Extensions. Topic Models: Mixed Membership Models for Text. Semi-Supervised Mixed Membership Models. Special Methodology for Sequence and Rank Data. Mixed Membership Models for Networks. Index.
Reihe/Serie | Chapman & Hall/CRC Handbooks of Modern Statistical Methods |
---|---|
Zusatzinfo | 61 Tables, black and white; 143 Illustrations, color |
Verlagsort | Bosa Roca |
Sprache | englisch |
Maße | 178 x 254 mm |
Gewicht | 1474 g |
Themenwelt | Geisteswissenschaften ► Psychologie ► Allgemeine Psychologie |
Mathematik / Informatik ► Informatik ► Theorie / Studium | |
Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
Technik ► Elektrotechnik / Energietechnik | |
Technik ► Umwelttechnik / Biotechnologie | |
ISBN-10 | 1-4665-0408-0 / 1466504080 |
ISBN-13 | 978-1-4665-0408-0 / 9781466504080 |
Zustand | Neuware |
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