Variable selection for single-index varying-coefficients models with applications to synergistic G × E interactions [0.03%]
单指数变系数模型的变量选择及其在协同基因与环境交互作用中的应用
Shunjie Guan,Mingtao Zhao,Yuehua Cui
Shunjie Guan
Epidemiological evidence suggests that simultaneous exposures to multiple environmental risk factors (Es) can increase disease risk larger than the additive effect of individual exposure acting alone. The interaction between a gene and mult...
Selecting massive variables using an iterated conditional modes/medians algorithm [0.03%]
利用迭代条件模式/中位数算法选择大量变量
Vitara Pungpapong,Min Zhang,Dabao Zhang
Vitara Pungpapong
Empirical Bayes methods are designed in selecting massive variables, which may be inter-connected following certain hierarchical structures, because of three attributes: taking prior information on model parameters, allowing data-driven hyp...
Asymmetric canonical correlation analysis of Riemannian and high-dimensional data [0.03%]
黎曼和高维数据的非对称典范相关分析
James Buenfil,Eardi Lila
James Buenfil
In this paper, we introduce a novel statistical model for the integrative analysis of Riemannian-valued functional data and high-dimensional data. We apply this model to explore the dependence structure between each subject's dynamic functi...
Yiling Huang,Snigdha Panigrahi,Walter Dempsey
Yiling Huang
Neighborhood selection is a widely used method used for estimating the support set of sparse precision matrices, which helps determine the conditional dependence structure in undirected graphical models. However, reporting only point estima...
Jonathan H Huggins,Jeffrey W Miller
Jonathan H Huggins
Under model misspecification, it is known that Bayesian posteriors often do not properly quantify uncertainty about true or pseudo-true parameters. Even more fundamentally, misspecification leads to a lack of reproducibility in the sense th...
Regression analysis of semiparametric Cox-Aalen transformation models with partly interval-censored data [0.03%]
半参数Cox-Aalen变换模型的部分区间删失数据的回归分析
Xi Ninga,Yanqing Sun,Yinghao Pan et al.
Xi Ninga et al.
Partly interval-censored data, comprising exact and intervalcensored observations, are prevalent in biomedical, clinical, and epidemiological studies. This paper studies a flexible class of the semiparametric Cox-Aalen transformation models...
Tianyu Zhang,Noah Simon
Tianyu Zhang
Estimation of a conditional mean (linking a set of features to an outcome of interest) is a fundamental statistical task. While there is an appeal to flexible nonparametric procedures, effective estimation in many classical nonparametric fu...
Robust improvement of efficiency using information on covariate distribution [0.03%]
利用协变量分布信息改进估计效率的稳健方法
Lu Mao
Lu Mao
The marginal inference of an outcome variable can be improved by closely related covariates with a structured distribution. This differs from standard covariate adjustment in randomized trials, which exploits covariate-treatment independenc...
Bohao Tang,Sandipan Pramanik,Yi Zhao et al.
Bohao Tang et al.
In this manuscript, we study scalar-on-distribution regression; that is, instances where subject-specific distributions or densities are the covariates, related to a scalar outcome via a regression model. In practice, only repeated measures...
Online inference in high-dimensional generalized linear models with streaming data [0.03%]
在线高维广义线性模型的流数据推理
Lan Luo,Ruijian Han,Yuanyuan Lin et al.
Lan Luo et al.
In this paper we develop an online statistical inference approach for high-dimensional generalized linear models with streaming data for realtime estimation and inference. We propose an online debiased lasso method that aligns with the data...