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About this product
Product Identifiers
PublisherDover Publications, Incorporated
ISBN-100486445143
ISBN-139780486445144
eBay Product ID (ePID)46871259
Product Key Features
Number of Pages352 Pages
LanguageEnglish
Publication NameProbabilistic Metric Spaces
Publication Year2011
SubjectProbability & Statistics / General, Applied
TypeTextbook
Subject AreaMathematics
AuthorB. Schweizer, A. Sklar
SeriesDover Books on Mathematics Ser.
FormatPerfect
Dimensions
Item Height0.7 in
Item Weight12.6 Oz
Item Length8.6 in
Item Width6.6 in
Additional Product Features
Intended AudienceCollege Audience
LCCN2005-054815
Dewey Edition22
IllustratedYes
Dewey Decimal514.32
Table Of ContentPreface to Dover EditionPrefaceSpecial Symbols1. Introduction and Historical Survey2. Preliminaries3. Metric and Topical Structures4. Distribution Functions5. Associativity6. Copulas7. Triangle Functions8. Probabilistic Metric Spaces9. Random Metric Spaces10. Distribution-Generated Spaces11. Transformation-Generated Spaces12. The Strong Topology13. Profile Functions14. Betweenness15. SupplementsReferencesIndexErrataNotesSupplementary References
SynopsisThis non-classical treatment focuses on developing aspects that differ from the theory of ordinary metric spaces, working directly with probability distribution functions rather than random variables. Topics include special classes of probabilistic metric spaces, topologies, and several related structures, such as probabilistic normed and inner-product spaces. 1983 edition, updated with 3 new appendixes. Includes 17 illustrations., Topics include special classes of probabilistic metric spaces, topologies, and several related structures, such as probabilistic normed and inner-product spaces. 1983 edition, updated with 3 new appendixes. Includes 17 illustrations., This distinctly nonclassical treatment focuses on developing aspects that differ from the theory of ordinary metric spaces, working directly with probability distribution functions rather than random variables. The two-part treatment begins with an overview that discusses the theory's historical evolution, followed by a development of related mathematical machinery. The presentation defines all needed concepts, states all necessary results, and provides relevant proofs. The second part opens with definitions of probabilistic metric spaces and proceeds to examinations of special classes of probabilistic metric spaces, topologies, and several related structures, such as probabilistic normed and inner-product spaces. Throughout, the authors focus on developing aspects that differ from the theory of ordinary metric spaces, rather than simply transferring known metric space results to a more general setting.