Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions

Neural Information Processing Systems 

This paper investigates the asymptotic distribution of the maximum-likelihood estimate (MLE) in multinomial logistic models in the high-dimensional regime where dimension and sample size are of the same order.

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