Scalable Bayesian Variable Selection Using Nonlocal Prior Densities in Ultrahigh-dimensional Settings [0.03%]
超高维设置下基于非局部先验的可扩展贝叶斯变量选择方法
Minsuk Shin,Anirban Bhattacharya,Valen E Johnson
Minsuk Shin
Bayesian model selection procedures based on nonlocal alternative prior densities are extended to ultrahigh dimensional settings and compared to other variable selection procedures using precision-recall curves. Variable selection procedure...
Siyuan Zhou,Debashis Paul,Jie Peng
Siyuan Zhou
We consider modeling non-autonomous dynamical systems for a group of subjects. The proposed model involves a common baseline gradient function and a multiplicative time-dependent subject-specific effect that accounts for phase and amplitude...
Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interactions [0.03%]
高维线性回归中的两样本检验及其在交互作用检测中的应用
Yin Xia,Tianxi Cai,T Tony Cai
Yin Xia
Motivated by applications in genomics, we consider in this paper global and multiple testing for the comparisons of two high-dimensional linear regression models. A procedure for testing the equality of the two regression vectors globally i...
Predicting disease Risk by Transformation Models in the Presence of Unspecified Subgroup Membership [0.03%]
转换模型在亚组成员资格不明时对疾病风险的预测能力研究
Qianqian Wang,Yanyuan Ma,Yuanjia Wang
Qianqian Wang
Some biomedical studies lead to mixture data. When a discrete covariate defining subgroup membership is missing for some of the subjects in a study, the distribution of the outcome follows a mixture distribution of the subgroup-specific dis...
Baosheng Liang,Xingwei Tong,Donglin Zeng et al.
Baosheng Liang et al.
In many clinical studies, patients may be asked to report their medication adherence, presence of side effects, substance use, and hospitalization information during the study period. However, the exact occurrence time of these recurrent ev...
A MULTIVARIATE GAUSSIAN PROCESS FACTOR MODEL FOR HAND SHAPE DURING REACH-TO-GRASP MOVEMENTS [0.03%]
用于到达并抓握过程中手形变化的多元高斯过程因子模型
Lucia Castellanos,Vincent Q Vu,Sagi Perel et al.
Lucia Castellanos et al.
We propose a Multivariate Gaussian Process Factor Model to estimate low dimensional spatio-temporal patterns of finger motion in repeated reach-to-grasp movements. Our model decomposes and reduces the dimensionality of variation of the mult...
Runze Li,Jingyuan Liu,Lejia Lou
Runze Li
Partial correlation based variable selection method was proposed for normal linear regression models by Bühlmann, Kalisch and Maathuis (2010) as a comparable alternative method to regularization methods for variable selection. This paper a...
CONTROL FUNCTION ASSISTED IPW ESTIMATION WITH A SECONDARY OUTCOME IN CASE-CONTROL STUDIES [0.03%]
病例对照研究中借助辅助信息的逆概率加权法估计次要结局效应
Tamar Sofer,Marilyn C Cornelis,Peter Kraft et al.
Tamar Sofer et al.
Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcome...
Tamar Sofer,Lee Dicker,Xihong Lin
Tamar Sofer
We consider variable selection for high-dimensional multivariate regression using penalized likelihoods when the number of outcomes and the number of covariates might be large. To account for within-subject correlation, we consider variable...
T Tony Cai,Hongzhe Li,Weidong Liu et al.
T Tony Cai et al.
Motivated by analysis of gene expression data measured in different tissues or disease states, we consider joint estimation of multiple precision matrices to effectively utilize the partially shared graphical structures of the corresponding...