本研究针对高维多元广义线性模型(Multivariate General Linear Model, MGLM)中的参数矩阵检验难题，来自国内的研究团队开发了创新的统计检验方法。通过构建新型检验统计量，解决了传统方法在大维度数据场景下的失效问题，为基因组学等高通量数据分析提供了可靠工具。

This is a preview. Log in through your library . Abstract Generalized linear models are popular for modelling a large variety of data. We consider variable selection through penalized methods by ...

This article considers the problem of inference for nested least squares averaging estimators. We study the asymptotic behavior of the Mallows model averaging estimator (MMA; Hansen, 2007) and the ...