Fundamentals of Statistics with Fuzzy Data [electronic resource] / by Hung Nguyen, Berlin Wu.

By: Nguyen, Hung [author.]Contributor(s): Wu, Berlin [author.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Studies in Fuzziness and Soft Computing: 198Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006Description: IX, 195 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540316978Subject(s): Engineering | Artificial intelligence | Mathematics | Statistics | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics) | Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences | Applications of MathematicsAdditional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
Introduction -- Set-valued Data -- Modeling of fuzzy data -- Random fuzzy sets -- Aspect of statistical Inference -- Convergence of random fuzzy sets -- Fuzzy Statistical Analysis and Estimation -- Testing Hypothesis with Fuzzy Data -- Fuzzy Time Series Analysis and Forecasting.
In: Springer eBooksSummary: This research monograph presents basic foundational aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Fuzzy data are modeled as observations from random fuzzy sets. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The monograph also aims at motivating statisticians to look at fuzzy statistics to enlarge the domain of applicability of statistics in general. HUNG T. NGUYEN is a professor of Mathematical Sciences at New Mexico State University, USA. BERLIN WU is a professor of Mathematical Sciences at National Chengchi University, Taipei, Taiwan.
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Introduction -- Set-valued Data -- Modeling of fuzzy data -- Random fuzzy sets -- Aspect of statistical Inference -- Convergence of random fuzzy sets -- Fuzzy Statistical Analysis and Estimation -- Testing Hypothesis with Fuzzy Data -- Fuzzy Time Series Analysis and Forecasting.

This research monograph presents basic foundational aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Fuzzy data are modeled as observations from random fuzzy sets. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The monograph also aims at motivating statisticians to look at fuzzy statistics to enlarge the domain of applicability of statistics in general. HUNG T. NGUYEN is a professor of Mathematical Sciences at New Mexico State University, USA. BERLIN WU is a professor of Mathematical Sciences at National Chengchi University, Taipei, Taiwan.

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