Robust gene-environment interaction analysis using penalized trimmed regression

In biomedical and epidemiological studies, gene-environment (G-E) interactions have been shown to importantly contribute to the etiology and progression of many complex diseases. Most existing approaches for identifying G-E interactions are limited by the lack of robustness against outliers/contamin...

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Bibliographische Detailangaben

Veröffentlicht in:	Journal of statistical computation and simulation. - 1999. - 88(2018), 18 vom: 04., Seite 3502-3528
1. Verfasser:	Xu, Yaqing (VerfasserIn)
Weitere Verfasser:	Wu, Mengyun, Ma, Shuangge, Ahmed, Syed Ejaz
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2018
Zugriff auf das übergeordnete Werk:	Journal of statistical computation and simulation
Schlagworte:	Journal Article G-E interaction Penalized selection Robustness Trimmed regression