Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interaction

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：liongliong600

【摘要】

：

【作者】

：

Yin Xia Tianxi Cai Tony Cai

【机构】

：

Fudan University,200433,China Department of Biost

【出处】

：

上海交通大学

【发表日期】

：

2016年4期

【关键词】

：

False discovery proportion false discovery rate high-dimensional linear regressi

下载到本地 , 更方便阅读

下载此文赞助VIP

声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架

论文部分内容阅读

　　Motivated by important applications in genomics,we consider in this talk global and coordinatewise tests for the comparisons of two high-dimensional linear regression models.A procedure for testing the equality of the two regression vectors globally is proposed and shown to be particularly powerful against sparse alternatives.

其他文献

Automatic Shape-constrained Nonparametric Regression

Shape information such as monotonicity and convexity of regression functions,if available,can be incorporated in nonparametric regression to improve estimation accuracy.However,in practice,the functio

会议

B-splineConstrained nonparametric regressionPenalizationShape

A Bayesian Hierarchical Summary Receiver Operating Characteristic Model for Network Meta-analysis of

In studies evaluating the accuracy of diagnostic tests,three designs are commonly used:(1)the crossover design;(2)the randomized design; and(3)the non-comparative design.Existing methods on meta-analy

会议

Diagnostic testsBayesian hierarchical modelMissing dataMultiple tests compari

Model-Assisted Approach for Estimating Average Causal Effect:A Bayesian Perspective

Inferring a causal relationship is an important task in both social science and health research.In an observational study,unlike a randomized experiment,treatment assignment is likely to be confounded

会议

Potential Outcome FrameworkBayesian NonparametricsGaussian ProcessCausal Infe

A New Scope of Penalized Empirical Likelihood with High-Dimensional Estimating Equations

Statistical inferences with empirical likelihood(EL)are appealing and effective especially in conjunction with estimating equations through which useful data information can be adaptively and flexibly

会议

Empirical likelihoodEstimating equationsHigh-dimensional statistical methodsM

Collaborative targeted learning using regression shrinkage

Causal inference practitioners are routinely presented with the challenge of wanting to adjust for large numbers of covariates despite limited sample sizes.Collaborative Targeted Maximum Likelihood Es

会议

causal inferencetargeted learningvariable selectionpenalized regressionsemip

On Dynamic Nearest-Neighbor Gaussian Process Models for High-Dimensional Spatiotemporal Data

With the growing capabilities of Geographic Information Systems(GIS)and user-friendly software,statisticians today routinely encounter geographically referenced data containing observations from a lar

会议

Bayesian inferenceGaussian processesHierarchical modelsScalable processesSpa

Novel integrated systems approach discovers cell specific genetic-transcriptomic-methylation network

Most tissues consist of multiple cell types.Global profiling of gene expression and methylation results from the convolution of multiple cell type specific expressions and methylations that lead to he

会议

Gene expression deconvolutionmethylation deconvolutionnonnegative matrix decom

Deep learning in multi-level causal genomic-epigenomic network analysis and its application to Alzhe

The next generation of genomic,sensing and image technologies and the precision medicine project will produce deeper and deeper multiple omic,physiological,environmental and phenotypic data with milli

会议

covariance operatorFunctional canonical correlation analysiscausal inferenceg

Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity

In this paper,we study the problem of testing the mean vectors of high dimensional data in both one-sample and two-sample cases.The proposed testing procedures employ maximum-type statistics and the p

会议

Feature screeningHigh dimensionHypothesis testingNormal approximationParamet

THE R PACKAGE THREGS TO IMPLEMENT THRESHOLD REGRESSION MODEL IN THE SETTING OF COMPLEX SURVEYS

This paper introduces a new R package called thregS,which is for the estimation procedure of a threshold regression model for complex surveys.The threshold regression method utilized in this package i

会议

first-hitting-timesurvival analysisthregSthreshold regressioncomplex surveys

Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interaction

与本文相关的学术论文