Group feature screening for ultrahigh-dimensional data missing at random

Group feature screening for ultrahigh-dimensional data missing at random

Statistical inference for missing data is common in data analysis, and there are still widespread cases of missing data in big data. The literature has discussed the practicability of two-stage feature screening with categorical covariates missing at random (IMCSIS). Therefore, we propose group feat...

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Bibliographic Details
Main Authors: Hanji He, Meini Li, Guangming Deng
Format: Article
Language:English
Published: AIMS Press 2024-01-01
Series:AIMS Mathematics
Subjects:
group feature screening
sure screening property
chi-square statistic
missing data
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2024197?viewType=HTML

Internet

https://www.aimspress.com/article/doi/10.3934/math.2024197?viewType=HTML

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