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在高维回归中选择变量的简单信息标准

Matthieu Pluntz1, Cyril Dalmasso2, Pascale Tubert-Bitter1

  • 1High-Dimensional Biostatistics for Drug Safety and Genomics, CESP, Université Paris-Saclay, UVSQ, Université Paris-Sud, Inserm, Villejuif, France.

Statistics in medicine
|December 12, 2024
PubMed
概括

我们介绍了扩展的AIC (EAIC),这是一个用于高维回归中稀疏模型选择的新标准. 与AIC和BIC不同,EAIC控制虚假阳性率,提高了变量选择的准确性.

关键词:
在FWER中控制控制.拉索·拉索 (Lasso) 是一个高维回归的高维回归方法信息 信息标准 信息标准药物监督和药物监督选择变量的选择变量.

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