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Robust Logistic Regression/Evidence
Method evidence record

Robust Logistic Regression

Robust Logistic Regression is a variant of logistic regression that is resistant to outliers and leverage points, fitting a binary or categorical outcome with Mallows-type weighted estimation. The robust framework for generalized linear models was developed by Cantoni and Ronchetti (2001), with a weighting approach later refined by Bondell (2008).

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Robust Logistic Regression (Mallows-Type Weighted Estimation)
Taxonomic method record · regression-model / statistics
  • Cantoni, E. & Ronchetti, E. (2001). Robust Inference for Generalized Linear Models. Journal of the American Statistical Association, 96(455), 1022-1030. · DOI 10.1198/016214501753209004
  • Bondell, H. D. (2008). Robust Logistic Regression Using a Weighting Approach. Biometrics, 64(2), 421-427. · URL
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Related methods

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See alsoLogistic Regressionmachine-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.Same method familyRobust Time Series Analysismachine-suggested · Relational suggestion, not evidence.

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Sources

2 recorded citations, copied from the method source record.

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