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M-Estimator/Ushahidi
Rekodi ya ushahidi wa mbinu

M-Estimator

M-estimators are a robust generalisation of maximum likelihood estimation, formalised in the work of Peter J. Huber (Huber & Ronchetti, 2009). Instead of squaring every residual, they apply a bounded loss function so that large residuals from outliers are down-weighted rather than allowed to dominate the fit.

Sources recorded, not reviewed

Rekodi ya chanzo

Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.

M-Estimators (Robust Regression)
Rekodi ya mbinu ya kiajenda · regression-model / statistics
  • Huber, P. J., & Ronchetti, E. M. (2009). Robust Statistics (2nd ed.). Wiley. · URL
  • Maronna, R. A., Martin, R. D., Yohai, V. J., & Salibián-Barrera, M. (2019). Robust Statistics: Theory and Methods (with R) (2nd ed.). Wiley. · URL
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Same method familyLeast Trimmed Squaresmachine-suggested · Relational suggestion, not evidence.Same method familyMM-Estimatormachine-suggested · Relational suggestion, not evidence.Same method familyOLS Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyQuantile Regressionmachine-suggested · Relational suggestion, not evidence.See alsoRidge Regressionmachine-suggested · Relational suggestion, not evidence.

Hali ya ushahidi

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

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