ABSTRACT
Incorporating more than 20 years of the editors' and contributors' statistical work in mixed membership modeling, this handbook shows 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, readers will discover how to characterize complex multivariate data in a range of areas.
TABLE OF CONTENTS
part 1|2 pages
Part 1 Mixed Membership: Setting the Stage
part 2|2 pages
Part 2 The Grade of Membership Model and Its Extensions
part 3|2 pages
Part 3 Topic Models: Mixed Membership Models for Text
part 4|2 pages
Semi-Supervised Mixed Membership Models
part 5|2 pages
Part 5 Special Methodology for Sequence and Rank Data
part 6|2 pages
Part 6 Mixed Membership Models for Networks