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• W4313472004 abstract "The optimal subsampling is an statistical methodology for generalized linear models (GLMs) to make inference quickly about parameter estimation in massive data regression. Existing literature only considers bounded covariates. In this paper, the asymptotic normality of the subsampling M-estimator based on the Fisher information matrix is obtained. Then, we study the asymptotic properties of subsampling estimators of unbounded GLMs with nonnatural links, including conditional asymptotic properties and unconditional asymptotic properties." @default.
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• W4313472004 date "2022-12-31" @default.
• W4313472004 modified "2023-09-26" @default.
• W4313472004 title "Asymptotics of Subsampling for Generalized Linear Regression Models under Unbounded Design" @default.
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• W4313472004 doi "https://doi.org/10.3390/e25010084" @default.
• W4313472004 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36673225" @default.
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