Component models for fuzzy data

DOI10.1007/s11336-003-1105-1zbMath1306.62400OpenAlexW2076603105MaRDI QIDQ2260987

Pierpaolo D'Urso, Renato Coppi, Paolo E. Giordani

Publication date: 6 March 2015

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-003-1105-1

zbMATH Keywords

principal component analysisfuzzy dataleast squares approachinformational paradigmdistance measure for fuzzy data

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to psychology (62P15)

Related Items (14)

Three-way analysis of imprecise data ⋮ Two- and three-way component models for lr fuzzy data in a possibilistic framework ⋮ Possibilistic and fuzzy clustering methods for robust analysis of non-precise data ⋮ A psychometric modeling approach to fuzzy rating data ⋮ Fuzzy and possibilistic clustering for fuzzy data ⋮ Change point analysis of imprecise time series ⋮ Fuzzy clustering of fuzzy data based on robust loss functions and ordered weighted averaging ⋮ Principal component histograms from interval-valued observations ⋮ Management of uncertainty in statistical reasoning: the case of regression analysis ⋮ The fuzzy characterizing function of the distribution of a random fuzzy number ⋮ Simulation of fuzzy random variables ⋮ Principal component analysis for interval‐valued observations ⋮ A parameterized \(L^2\) metric between fuzzy numbers and its parameter interpretation ⋮ Self-organizing maps for imprecise data

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