Category-Adaptive Variable Screening for Ultra-High Dimensional Heterogeneous Categorical Data

DOI10.1080/01621459.2019.1573734zbMath1445.62020OpenAlexW2921286874WikidataQ128270615 ScholiaQ128270615MaRDI QIDQ5130620

Jinhan Xie, Xiaodong Yan, Yuanyuan Lin, Nian Sheng Tang

Publication date: 28 October 2020

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2019.1573734

zbMATH Keywords

heterogeneityresponse-selective samplingfeature screeningultra-high dimensional datacategorical response

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Sampling theory, sample surveys (62D05)

Related Items (9)

Partition-based feature screening for categorical data via RKHS embeddings ⋮ Hierarchical cancer heterogeneity analysis based on histopathological imaging features ⋮ Hybrid Hard-Soft Screening for High-dimensional Latent Class Analysis ⋮ Model-Free Conditional Feature Screening with FDR Control ⋮ Post-selection Inference of High-dimensional Logistic Regression Under Case–Control Design ⋮ Conditional characteristic feature screening for massive imbalanced data ⋮ Sparse overlapped linear discriminant analysis ⋮ Unnamed Item ⋮ Composite quantile regression for ultra-high dimensional semiparametric model averaging

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