Detection of outliers and robust estimation using fuzzy clustering

DOI10.1016/0167-9473(93)90218-IzbMath0937.62525OpenAlexW1967318993MaRDI QIDQ2563634

Isak Nethanël Gath, Bernard van Cutsem

Publication date: 31 August 1997

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(93)90218-i

zbMATH Keywords

outliersperformance measuresfuzzy clusteringrobust estimationjackknife

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (6)

Fuzzy-weighted estimation in ridge regression analysis ⋮ Minimum Spanning Tree-Resembling algorithm for Clusters, Outliers and Hubs ⋮ A bilateral fuzzy support vector machine hybridizing the Gaussian mixture model ⋮ Weighted quasi-likelihood estimation based on fuzzy clustering analysis method and dimension reduction technique ⋮ An application of weighted bootstrap method in semi-parametric model ⋮ Fuzzy weighted scaled coefficients in semi-parametric model

Cites Work

• Rejection of Outliers
• Fuzzy clustering for the estimation of the parameters of the components of mixtures of normal distributions
• Mixture Models, Outliers, and the EM Algorithm
• On the Detection of Many Outliers
• A Class of Nonparametric Tests for Independence in Bivariate Populations
• Some Concepts of Dependence
• Treatment of outliers in samples of size three
• Estimating the components of a mixture of normal distributions
• Sample Criteria for Testing Outlying Observations
• THE DISTRIBUTION OF THE RATIO, IN A SINGLE NORMAL SAMPLE, OF RANGE TO STANDARD DEVIATION
• Cluster Validity with Fuzzy Sets
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