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Robustná klasterová analýza (TCLUST)×Robustná regresia pomocou W-odhadu (Tukeyho bipolárna / Welschova)×
OdborŠtatistikaŠtatistika
RodinaRegression modelRegression model
Rok vzniku20081974
TvorcaGarcía-Escudero, Gordaliza, Matrán & Mayo-Iscar (TCLUST)Beaton & Tukey (bisquare weight); Welsch (Welsch weight)
TypRobust model-based clusteringRobust regression (redescending M-estimator)
Pôvodný zdrojGarcía-Escudero, L. A., Gordaliza, A., Matrán, C., & Mayo-Iscar, A. (2008). A General Trimming Approach to Robust Cluster Analysis. The Annals of Statistics, 36(3), 1324-1345. DOI ↗Beaton, A. E. & Tukey, J. W. (1974). The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data. Technometrics, 16(2), 147-185. DOI ↗
Ďalšie názvyTCLUST, trimmed clustering, robust clustering, Robust Küme Analizi (TCLUST)Tukey bisquare M-estimator, Welsch M-estimator, redescending M-estimator, W-Tahmin Edici (Welsch / Tukey Bisquare)
Príbuzné54
ZhrnutieRobust Cluster Analysis is a trimmed model-based clustering method, introduced by García-Escudero and colleagues in 2008, that partitions continuous multivariate data into clusters while resisting the influence of outliers and noise. By setting aside a fraction of the most discordant observations, it keeps the recovered cluster structure from being contaminated by stray points.The W-estimator is a family of robust M-estimator variants for linear regression that use the Tukey bisquare and Welsch weight functions, introduced in the line of work going back to Beaton and Tukey (1974). Because its weights fall rapidly toward zero as a residual grows, it resists outliers more strongly than the Huber M-estimator.
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ScholarGatePorovnať metódy: Robust Cluster Analysis · W-Estimator. Získané 2026-06-18 z https://scholargate.app/sk/compare