Detection of outliers and robust estimation using fuzzy clustering
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Publication:2563634
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
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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