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Books > Professional & Technical > Energy technology & engineering > Electrical engineering
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Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis (Paperback)
Loot Price: R1,706
Discovery Miles 17 060
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Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis (Paperback)
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A New Way of Analyzing Object Data from a Nonparametric Viewpoint
Nonparametric Statistics on Manifolds and Their Applications to
Object Data Analysis provides one of the first thorough treatments
of the theory and methodology for analyzing data on manifolds. It
also presents in-depth applications to practical problems arising
in a variety of fields, including statistics, medical imaging,
computer vision, pattern recognition, and bioinformatics. The book
begins with a survey of illustrative examples of object data before
moving to a review of concepts from mathematical statistics,
differential geometry, and topology. The authors next describe
theory and methods for working on various manifolds, giving a
historical perspective of concepts from mathematics and statistics.
They then present problems from a wide variety of areas, including
diffusion tensor imaging, similarity shape analysis, directional
data analysis, and projective shape analysis for machine vision.
The book concludes with a discussion of current related research
and graduate-level teaching topics as well as considerations
related to computational statistics. Researchers in diverse fields
must combine statistical methodology with concepts from projective
geometry, differential geometry, and topology to analyze data
objects arising from non-Euclidean object spaces. An expert-driven
guide to this approach, this book covers the general nonparametric
theory for analyzing data on manifolds, methods for working with
specific spaces, and extensive applications to practical research
problems. These problems show how object data analysis opens a
formidable door to the realm of big data analysis.
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