Fuzzy classification maximum likelihood algorithms for mixed-Weibull distributions

DOI10.1007/S00500-007-0266-8zbMath1140.62329OpenAlexW1969679066MaRDI QIDQ934917

Yen-Chang Chang, Shun-Chin Chuang, Wen-Liang Hung

Publication date: 30 July 2008

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-007-0266-8

zbMATH Keywords

EM algorithmFuzzy class modelFuzzy clustering algorithm

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (3)

A ROBUST FUZZY CLASSIFICATION MAXIMUM LIKELIHOOD CLUSTERING FRAMEWORK ⋮ Comparison between method of moments and entropy regularization algorithm applied to parameter estimation for mixed-Weibull distribution ⋮ Detecting change-points for shifts in mean and variance using fuzzy classification maximum likelihood change-point algorithms

Cites Work

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• Extended Weibull type distribution and finite mixture of distributions
• On a class of fuzzy classification maximum likelihood procedures
• Estimation of parameters in latent class models using fuzzy clustering algorithms
• Nonparametric Bayesian survival analysis using mixtures of Weibull distributions
• Graphical representation of two mixed-Weibull distributions
• Maximum likelihood estimates, from censored data, for mixed-Weibull distributions
• Finite mixture models
• Fuzzy sets

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