Introduction to Random Sets
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€192.20
A01=Hung T. Nguyen
advanced undergraduate textbook
Author_Hung T. Nguyen
Belief Functions
Capacity Functional
Category=PBCH
Category=PBD
Category=PBT
Category=PBW
Category=PHU
choquet
Choquet Integral
Choquet Theorem
Closed Subsets
Compact Metric Space
Distribution Function
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
finite
Finite Random Set
function
Hausdorff Metric
Incidence Algebras
Infinite Order
integral
intelligent systems applications
law
Lim Inf
mathematical statistics
measure
Metric Space
Nonempty Compact Subsets
probability
Probability Laws
Probability Measure
Probability Sampling Design
Probability Sampling Plan
Radon Nikodym Derivative
Random Closed Sets
Random Experiment
Random Set
sampling
Separable Metric Space
Set Function
set-valued data analysis
space
statistical uncertainty modeling in engineering
stochastic modeling
uncertainty quantification
variable
Weak Convergence
Product details
- ISBN 9781584885191
- Weight: 498g
- Dimensions: 156 x 234mm
- Publication Date: 27 Mar 2006
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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The study of random sets is a large and rapidly growing area with connections to many areas of mathematics and applications in widely varying disciplines, from economics and decision theory to biostatistics and image analysis. The drawback to such diversity is that the research reports are scattered throughout the literature, with the result that in science and engineering, and even in the statistics community, the topic is not well known and much of the enormous potential of random sets remains untapped.
An Introduction to Random Sets provides a friendly but solid initiation into the theory of random sets. It builds the foundation for studying random set data, which, viewed as imprecise or incomplete observations, are ubiquitous in today's technological society. The author, widely known for his best-selling A First Course in Fuzzy Logic text as well as his pioneering work in random sets, explores motivations, such as coarse data analysis and uncertainty analysis in intelligent systems, for studying random sets as stochastic models. Other topics include random closed sets, related uncertainty measures, the Choquet integral, the convergence of capacity functionals, and the statistical framework for set-valued observations. An abundance of examples and exercises reinforce the concepts discussed.
Designed as a textbook for a course at the advanced undergraduate or beginning graduate level, this book will serve equally well for self-study and as a reference for researchers in fields such as statistics, mathematics, engineering, and computer science.
Nguyen, Hung T.
