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• W3113121104 abstract "Motivated by recent works on the high-dimensional logistic regression, we establish that the existence of the maximum likelihood estimate exhibits a phase transition for a wide range of generalized linear models with binary outcome and elliptical covariates. This extends a previous result of Cand`es and Sur who proved the phase transition for the logistic regression with Gaussian covariates. Our result reveals a rich structure in the phase transition phenomenon, which is simply overlooked by Gaussianity. The main tools for deriving the result are data separation, convex geometry and stochastic approximation. We also conduct simulation studies to corroborate our theoretical findings, and explore other features of the problem." @default.
• W3113121104 created "2020-12-21" @default.
• W3113121104 creator A5058487048 @default.
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• W3113121104 date "2019-08-16" @default.
• W3113121104 modified "2023-10-16" @default.
• W3113121104 title "The existence of maximum likelihood estimate in high-dimensional binary response generalized linear models" @default.
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• W3113121104 doi "https://doi.org/10.48550/arxiv.1908.06208" @default.
• W3113121104 hasPublicationYear "2019" @default.
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