Eugene Katsevich,Chiara Sabatti,Marina Bogomolov
Eugene Katsevich
Scientific hypotheses in a variety of applications have domain-specific structures, such as the tree structure of the International Classification of Diseases (ICD), the directed acyclic graph structure of the Gene Ontology (GO), or the spa...
Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages [0.03%]
大型向量自回归移动平均模型的稀疏识别与估计
Ines Wilms,Sumanta Basu,Jacob Bien et al.
Ines Wilms et al.
The Vector AutoRegressive Moving Average (VARMA) model is fundamental to the theory of multivariate time series; however, identifiability issues have led practitioners to abandon it in favor of the simpler but more restrictive Vector AutoRe...
Edward L Ionides,Kidus Asfaw,Joonha Park et al.
Edward L Ionides et al.
Bagging (i.e., bootstrap aggregating) involves combining an ensemble of bootstrap estimators. We consider bagging for inference from noisy or incomplete measurements on a collection of interacting stochastic dynamic systems. Each system is ...
Reinforced risk prediction with budget constraint using irregularly measured data from electronic health records [0.03%]
基于电子健康记录不规则测量数据的预算约束条件下风险预测方法研究
Yinghao Pan,Eric B Laber,Maureen A Smith et al.
Yinghao Pan et al.
Uncontrolled glycated hemoglobin (HbA1c) levels are associated with adverse events among complex diabetic patients. These adverse events present serious health risks to affected patients and are associated with significant financial costs. ...
Jie Zhou,Will Wei Sun,Jingfei Zhang et al.
Jie Zhou et al.
In modern data science, dynamic tensor data prevail in numerous applications. An important task is to characterize the relationship between dynamic tensor datasets and external covariates. However, the tensor data are often only partially o...
Evaluating Association Between Two Event Times with Observations Subject to Informative Censoring [0.03%]
具有信息删失观测值的两个事件时间之间关联性的评估方法研究
Dongdong Li,X Joan Hu,Rui Wang
Dongdong Li
This article is concerned with evaluating the association between two event times without specifying the joint distribution parametrically. This is particularly challenging when the observations on the event times are subject to informative...
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs [0.03%]
凸优化和非凸优化在随机设计下的有噪盲去卷积中都是最小最大最优的
Yuxin Chen,Jianqing Fan,Bingyan Wang et al.
Yuxin Chen et al.
We investigate the effectiveness of convex relaxation and nonconvex optimization in solving bilinear systems of equations under two different designs (i.e. a sort of random Fourier design and Gaussian design). Despite the wide applicability...
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...
Francesca Gasperoni,Alessandra Luati,Lucia Paci et al.
Francesca Gasperoni et al.
A simultaneous autoregressive score-driven model with autoregressive disturbances is developed for spatio-temporal data that may exhibit heavy tails. The model specification rests on a signal plus noise decomposition of a spatially filtered...
Discussion of "Confidence Intervals for Nonparametric Empirical Bayes Analysis" [0.03%]
非参数经验贝叶斯分析的置信区间讨论
Dongyue Xie,Matthew Stephens
Dongyue Xie