Comparison of Longitudinal Trajectories Using a High-dimensional Partial Linear Semiparametric Mixed-Effects Model [0.03%]
基于高维半参数混合效应模型的纵向数据轨迹比较分析方法研究
Sami Leon,Tong Tong Wu
Sami Leon
In longitudinal research, it is essential to compare sets of trajectories, commonly seen as changes over time in different treatment or patient groups. This paper presents a partial linear semiparametric mixed-effects model (PLSMM) for the ...
Zhe Zhang,Xiufan Yu,Runze Li
Zhe Zhang
This paper proposes an innovative double power-enhanced testing procedure for inference on high-dimensional linear hypotheses in high-dimensional regression models. Through a projection approach that aims to separate useful inferential info...
Xu Guo,Runze Li,Zhe Zhang et al.
Xu Guo et al.
This paper aims to develop an effective model-free inference procedure for high-dimensional data. We first reformulate the hypothesis testing problem via sufficient dimension reduction framework. With the aid of new reformulation, we propos...
Antik Chakraborty,Rihui Ou,David B Dunson
Antik Chakraborty
It has become increasingly common to collect high-dimensional binary response data; for example, with the emergence of new sampling techniques in ecology. In smaller dimensions, multivariate probit (MVP) models are routinely used for infere...
Zhanrui Cai,Jing Lei,Kathryn Roeder
Zhanrui Cai
Test of independence is of fundamental importance in modern data analysis, with broad applications in variable selection, graphical models, and causal inference. When the data is high dimensional and the potential dependence signal is spars...
Variable Selection for High-dimensional Nodal Attributes in Social Networks with Degree Heterogeneity [0.03%]
具有度异质性的社会网络中高维节点属性的选择变量问题
Jia Wang,Xizhen Cai,Xiaoyue Niu et al.
Jia Wang et al.
We consider a class of network models, in which the connection probability depends on ultrahigh-dimensional nodal covariates (homophily) and node-specific popularity (degree heterogeneity). A Bayesian method is proposed to select nodal feat...
Yudong Chen,Tengyao Wang,Richard J Samworth
Yudong Chen
We introduce and study two new inferential challenges associated with the sequential detection of change in a high-dimensional mean vector. First, we seek a confidence interval for the changepoint, and second, we estimate the set of indices...
Nonparametric two-sample tests of high dimensional mean vectors via random integration [0.03%]
高维均值向量的非参数双样本检验及其随机积分方法研究
Yunlu Jiang,Xueqin Wang,Canhong Wen et al.
Yunlu Jiang et al.
Testing the equality of the means in two samples is a fundamental statistical inferential problem. Most of the existing methods are based on the sum-of-squares or supremum statistics. They are possibly powerful in some situations, but not i...
Keyur H Desai,John D Storey
Keyur H Desai
A growing number of modern scientific problems in areas such as genomics, neurobiology, and spatial epidemiology involve the measurement and analysis of thousands of related features that may be stochastically dependent at arbitrarily stron...
Zhe Fei,Qi Zheng,Hyokyoung G Hong et al.
Zhe Fei et al.
With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper statistical inference. Censored quantile regression has emerged a...