方法证据记录
Robust Multinomial Logistic Regression
Robust multinomial logistic regression extends the standard multinomial logit model to handle outliers, influential observations, and mild misspecification of the response distribution. It replaces the conventional maximum likelihood score equations with bounded influence functions (M-estimation) or pairs maximum likelihood with sandwich variance estimators, so that a small fraction of anomalous cases cannot distort the estimated log-odds ratios across outcome categories.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Robust Multinomial Logistic Regression
分类方法记录 · 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
- Agresti, A. (2002). Categorical Data Analysis (2nd ed.). Wiley-Interscience. · ISBN 978-0471360933
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