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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)

Taksonomski zapis metode · regression-model / statistics

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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.