Article

Cross-Fitted Contamination-Aware Generalized Empirical-Bayes Liu Shrinkage for Multinomial Logit Models under Multicollinearity and Outliers

2026-08-06

Abstract excerpt

<title>Abstract</title> <p>Multinomial logit estimation can be unstable when predictors are nearly collinear and can be distorted by response miscoding and high-leverage observations. We develop a cross-fitted contamination-aware generalized empirical-Bayes Liu estimator (CF-CABLS-MNL) that combines weighted density-power-divergence estimation, a diagonal-dominant class-misclassification model, sandwich/Godambe g...

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Literature Corpus work: 897a75ab-1236-5f0f-88ee-36f29c43c26a
DOI: 10.21203/rs.3.rs-10599718/v1

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