Variable selection for inferential models with relatively high-dimensional data: Between method heterogeneity and covariate stability as adjuncts to robust selection

Research article (Scientific Reports, 2020) · cited 36× · AI/ML
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Variable selection for inferential models with relatively high-dimensional data: Between method heterogeneity and covariate stability as adjuncts to robust selection

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Variable selection for inferential models with relatively high-dimensional data: Between method heterogeneity and covariate stability as adjuncts to robust selection is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Variable selection for inferential models with relatively high-dimensional data: Between method heterogeneity and covariate stability as adjuncts to robust selection. Retrieved May 24, 2026, from https://4ort.xyz/entity/variable-selection-for-inferential-models-with-relatively-high-dimensional-data-between-method-heterogeneity-and-covaria
MLA “Variable selection for inferential models with relatively high-dimensional data: Between method heterogeneity and covariate stability as adjuncts to robust selection.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/variable-selection-for-inferential-models-with-relatively-high-dimensional-data-between-method-heterogeneity-and-covaria.
BibTeX @misc{4ortxyz_variable-selection-for-inferential-models-with-relatively-high-dimensional-data-between-method-heterogeneity-and-covaria_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Variable selection for inferential models with relatively high-dimensional data: Between method heterogeneity and covariate stability as adjuncts to robust selection}}, year = {2026}, url = {https://4ort.xyz/entity/variable-selection-for-inferential-models-with-relatively-high-dimensional-data-between-method-heterogeneity-and-covaria}, note = {Accessed: 2026-05-24}}
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