Feature screening for ultrahigh dimensional categorical data with covariates missing at random

DOI10.1016/j.csda.2019.106824OpenAlexW2967736187WikidataQ127375264 ScholiaQ127375264MaRDI QIDQ2008118

Jun Shao, Fang Fang, Lyu Ni

Publication date: 22 November 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2019.106824

zbMATH Keywords

missing at randomsure screening propertyPearson chi-square statisticfeature screeningmissing covariate

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

Model-free feature screening for ultrahigh dimensional data via a Pearson chi-square based index, A distribution-free test of independence based on a modified mean variance index, Empirical likelihood in single-index quantile regression with high dimensional and missing observations, Model averaging for multiple quantile regression with covariates missing at random

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