Analysis of variance for fuzzy data

DOI10.1080/00207720601157997zbMath1417.62209OpenAlexW2044747815MaRDI QIDQ3442672

Hsien-Chung Wu

Publication date: 18 May 2007

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207720601157997

zbMATH Keywords

optimizationfuzzy setsconfidence degreeanalysis of variance (ANOVA)pessimistic and optimistic degrees

Mathematics Subject Classification ID

Analysis of variance and covariance (ANOVA) (62J10) Fuzziness, and linear inference and regression (62J86)

Related Items (8)

Unnamed Item ⋮ The statistical inferences of fuzzy regression based on bootstrap techniques ⋮ Demand forecasting of perishable farm products using support vector machine ⋮ Unnamed Item ⋮ One-way ANOVA based on interval information ⋮ Linear Hypothesis Testing Based on Unbiased Fuzzy Estimators and Fuzzy Significance Level ⋮ A Practical Application of Fuzzy Analysis of Variance in Agriculture ⋮ Analysis of variance based on fuzzy observations

Cites Work

• Fuzzy hypothesis testing with hybrid data
• Ranking fuzzy numbers in the setting of possibility theory
• The fuzzy decision problem: An approach to the problem of testing statistical hypotheses with fuzzy information
• A note on the operativeness of Neyman-Pearson tests with fuzzy information
• The minimum inaccuracy estimates in \(\chi ^ 2\) tests for goodness of fit with fuzzy observations
• Fuzzy random variables - I. Definitions and theorems
• A fuzzy decision problem based on the generalized Neyman-Pearson criterion
• Fuzzy sets as a basis for a theory of possibility
• The concept of a linguistic variable and its application to approximate reasoning. I
• Testing fuzzy hypotheses with crisp data
• Bayesian sequential test for fuzzy parametric hypotheses from fuzzy information
• Testing statistical hypotheses with vague data
• Extension of fuzzy hypothesis testing with hybrid data
• Statistical tests optimally meeting certain fuzzy requirements on the power function and on the sample size
• Fuzzy sets
• Fuzzy random variables

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