Overview
- Discusses main topics of ranking applying partial order theory
- Is about how far simple order methods can be useful for the ordinal analysis of data matrices
- The reader will learn how to apply unclear methods in partial order analysis
- Includes supplementary material: sn.pub/extras
Part of the book series: Environmental and Ecological Statistics (ENES)
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Table of contents (18 chapters)
Reviews
From the reviews:
“The main aim of the book is to introduce the modern tools and methodologies of the so-called partial order ranking for prioritization of objects by many different characteristics. … is addressed to graduate students and specialists in environmental, ecological, and other applied sciences requiring ordering and prioritization of many objects by numerous characteristics. … these new methods of partial order analysis can be insightful and useful, and extend the regular tool-kit of statisticians applying more conventional methods of PCA, factor analysis, data clustering, and segmentation.” (Stan Lipovetsky, Technometrics, Vol. 54 (2), May, 2012)Authors and Affiliations
Bibliographic Information
Book Title: Ranking and Prioritization for Multi-indicator Systems
Book Subtitle: Introduction to Partial Order Applications
Authors: Rainer Brüggemann, Ganapati P. Patil
Series Title: Environmental and Ecological Statistics
DOI: https://doi.org/10.1007/978-1-4419-8477-7
Publisher: Springer New York, NY
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Hardcover ISBN: 978-1-4419-8476-0Published: 08 July 2011
Softcover ISBN: 978-1-4614-2968-5Published: 27 September 2013
eBook ISBN: 978-1-4419-8477-7Published: 08 July 2011
Series ISSN: 2363-9660
Series E-ISSN: 2363-9679
Edition Number: 1
Number of Pages: XXVI, 338
Topics: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics for Life Sciences, Medicine, Health Sciences