A unified framework of multiply robust estimation approaches for handling incomplete data [0.03%]
一种处理不完整数据的多重稳健估计方法的统一框架
Sixia Chen,David Haziza
Sixia Chen
Missing data occur frequently in practice. Inverse probability weighting and imputation are regarded as two important approaches for handling missing data. However, the validity of these approaches depends on underlying model assumptions. A...
Variable Selection in Bayesian Multiple Instance Regression using Shotgun Stochastic Search [0.03%]
基于Shotgun随机搜索的贝叶斯多重实例回归中的变量选择
Seongoh Park,Joungyoun Kim,Xinlei Wang et al.
Seongoh Park et al.
In multiple instance learning (MIL), a bag represents a sample that has a set of instances, each of which is described by a vector of explanatory variables, but the entire bag only has one label/response. Though many methods for MIL have be...
Estimation of [Formula: see text] Norm Penalized Models: A Statistical Treatment [0.03%]
[Formula: see text]范数惩罚模型的估计：一个统计处理方法
Yuan Yang,Christopher S McMahan,Yu-Bo Wang et al.
Yuan Yang et al.
Fitting penalized models for the purpose of merging the estimation and model selection problem has become commonplace in statistical practice. Of the various regularization strategies that can be leveraged to this end, the use of the l0 nor...
Xichen Mou,Dewei Wang
Xichen Mou
Human biomonitoring involves monitoring human health by measuring the accumulation of harmful chemicals, typically in specimens like blood samples. The high cost of chemical analysis has led researchers to adopt a cost-effective approach. T...
Hierarchical False Discovery Rate Control for High-dimensional Survival Analysis with Interactions [0.03%]
具有交互作用的高维生存分析的分层错误发现率控制方法
Weijuan Liang,Qingzhao Zhang,Shuangge Ma
Weijuan Liang
With the development of data collection techniques, analysis with a survival response and high-dimensional covariates has become routine. Here we consider an interaction model, which includes a set of low-dimensional covariates, a set of hi...
Dynamic risk score modeling for multiple longitudinal risk factors and survival [0.03%]
多重纵向风险因素和生存的动态风险评分模型
Cuihong Zhang,Jing Ning,Jianwen Cai et al.
Cuihong Zhang et al.
Modeling disease risk and survival using longitudinal risk factor trajectories is of interest in various clinical scenarios. The capacity to build a prognostic model using the trajectories of multiple longitudinal risk factors, in the prese...
Under-reported time-varying MINAR(1) process for modeling multivariate count series [0.03%]
用于多变量计数序列建模的未报告的时间变化MINAR(1)过程
Zeynab Aghabazaz,Iraj Kazemi
Zeynab Aghabazaz
A time-varying multivariate integer-valued autoregressive of order one (tvMINAR(1)) model is introduced for the non-stationary time series of correlated counts when under-reporting is likely present. A non-diagonal autoregression probabilit...
Haim Bar,Martin T Wells
Haim Bar
A mixture-model of beta distributions framework is introduced to identify significant correlations among P features when P is large. The method relies on theorems in convex geometry, which are used to show how to control the error rate of e...
Jonathan Kim,Brian J Sandri,Raghavendra B Rao et al.
Jonathan Kim et al.
A Bayesian approach to predict a continuous or binary outcome from data that are collected from multiple sources with a multi-way (i.e., multidimensional tensor) structure is described. As a motivating example, molecular data from multiple ...
Mediation Analysis for High-Dimensional Mediators and Outcomes with an Application to Multimodal Imaging Data [0.03%]
高维中介变量和结果的中介分析及其在多模态影像数据中的应用
Zhiwei Zhao,Chixiang Chen,Bhim Mani Adhikari et al.
Zhiwei Zhao et al.
Multimodal neuroimaging data have attracted increasing attention for brain research. An integrated analysis of multimodal neuroimaging data and behavioral or clinical measurements provides a promising approach for comprehensively and system...