Statistical methods for fuzzy data /

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Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be b...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Viertl, R. (Reinhard)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Chichester, West Sussex : Wiley, 2011.
Temas:
Fuzzy measure theory.
Fuzzy sets.
Mathematical statistics.
Mesures floues (Mathématiques)
Ensembles flous.
MATHEMATICS > Calculus.
MATHEMATICS > Mathematical Analysis.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Statistical Methods forFuzzy Data; Contents; Preface; Part I FUZZY INFORMATION; 1 Fuzzy data; 1.1 One-dimensional fuzzy data; 1.2 Vector-valued fuzzy data; 1.3 Fuzziness and variability; 1.4 Fuzziness and errors; 1.5 Problems; 2 Fuzzy numbers and fuzzy vectors; 2.1 Fuzzy numbers and characterizing functions; 2.2 Vectors of fuzzy numbers and fuzzy vectors; 2.3 Triangular norms; 2.4 Problems; 3 Mathematical operations for fuzzy quantities; 3.1 Functions of fuzzy variables; 3.2 Addition of fuzzy numbers; 3.3 Multiplication of fuzzy numbers; 3.4 Mean value of fuzzy numbers.

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