Buy Handbook Of Mixed Membership Models And Their Applications (Chapman & Hall/CRC

This site may earn a commission as part of the eBay Partner Network and Amazon Associates Program if you make a purchase through our links.

See Details on Ebay

Handbook of Mixed Membership Models and Their Applications (Chapman & Hall/CRC

The handbook spans more than 20 years of the editors' and contributors' statistical work in the field. 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.

100.44$ Buy It Now

Item	204782752769
Seller	simplybestprices-10to20dayshipping ( 476447 ⭐ ) 98.1% Location: Los Angeles, US, CA Accept Payments With ,
Shipping	See shipping cost, Ships to Australia, ...
Guarantee	eBay Money Back Guarantee
Condition	Brand New
EAN	9780367330842
UPC	9780367330842
ISBN	9780367330842
Book Title	Handbook of Mixed Membership Models and Their Appl
Item Length	25.2 cm

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 databasesPatterns in the progression of diseases and disabilities Combinations of topics covered by text documentsPolitical ideology or electorate voting patternsHeterogeneous 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.