Spike-and-slab least absolute shrinkage and selection operator generalized additive models and scalable algorithms for high-dimensional data analysis.

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第一作者： Boyi,Guo

第一单位： Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA.

作者： Boyi,Guo ^[1] ; Byron C,Jaeger ^[2] ; A K M Fazlur,Rahman ^[1] ; D Leann,Long ^[1] ; Nengjun,Yi ^[1]

作者单位： Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA. ^[1] Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. ^[2]

关键词 EM-coordinate decsent generalized additive models high-dimensional data predictive modeling scalablility spike-and-slab priors

主题词算法(Algorithms);贝叶斯定理(Bayes Theorem);计算机模拟(Computer Simulation);人类(Humans);蒙特卡罗法(Monte Carlo Method)

DOI 10.1002/sim.9483

PMID 35665524

发布时间 2023-08-02

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Statistics in medicine

2022年41卷20期

3899-3914页

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Spike-and-slab least absolute shrinkage and selection operator generalized additive models and scalable algorithms for high-dimensional data analysis.

Statistics in medicine

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Statistics in medicine

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Spike-and-slab least absolute shrinkage and selection operator generalized additive models and scalable algorithms for high-dimensional data analysis.

Statistics in medicine

相似文献

Statistics in medicine

相关期刊

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