Corrected optimal subsampling for a class of generalized linear measurement error models

Subsampling techniques have been promoted in massive data and can substantially reduce the computing time. However, existing subsampling techniques do not consider the case of dirty data, especially the inaccuracy of covariates due to measurement errors, which will lead to the inconsistent estimator...

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Bibliographic Details

Published in:	AIMS Mathematics
Main Authors:	Ruiyuan Chang, Xiuli Wang, Mingqiu Wang
Format:	Article
Language:	English
Published:	AIMS Press 2025-02-01
Subjects:	a-optimality criteria generalized linear models l-optimality criteria massive data measurement errors optimal subsampling
Online Access:	https://www.aimspress.com/article/doi/10.3934/math.2025203