Handbook Of Mixed Membership Models And Their Applications


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Handbook of Mixed Membership Models and Their Applications


Handbook of Mixed Membership Models and Their Applications

Author: Edoardo M. Airoldi

language: en

Publisher: CRC Press

Release Date: 2014-11-06


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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.

Handbook of Mixed Membership Models and Their Applications


Handbook of Mixed Membership Models and Their Applications

Author: Edoardo M. Airoldi

language: en

Publisher: CRC Press

Release Date: 2014-11-06


DOWNLOAD





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.

Innovative Assessment of Collaboration


Innovative Assessment of Collaboration

Author: Alina A. von Davier

language: en

Publisher: Springer

Release Date: 2017-04-04


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This edited volume provides a platform for experts from various fields to introduce and discuss their different perspectives on the topic of teamwork and collaborative problem solving. It brings together researchers in organizational teaming, educational collaboration, tutoring, simulation, and gaming as well as those involved in statistical and psychometric process modelling. This book seeks to channel this expertise towards advances in the measurement and assessment of cognitive and non-cognitive skills of individuals and teams.