Yiling Huang,Snigdha Panigrahi,Walter Dempsey
Yiling Huang
Neighborhood selection is a widely used method used for estimating the support set of sparse precision matrices, which helps determine the conditional dependence structure in undirected graphical models. However, reporting only point estima...
Jonathan H Huggins,Jeffrey W Miller
Jonathan H Huggins
Under model misspecification, it is known that Bayesian posteriors often do not properly quantify uncertainty about true or pseudo-true parameters. Even more fundamentally, misspecification leads to a lack of reproducibility in the sense th...
Regression analysis of semiparametric Cox-Aalen transformation models with partly interval-censored data [0.03%]
半参数Cox-Aalen变换模型的部分区间删失数据的回归分析
Xi Ninga,Yanqing Sun,Yinghao Pan et al.
Xi Ninga et al.
Partly interval-censored data, comprising exact and intervalcensored observations, are prevalent in biomedical, clinical, and epidemiological studies. This paper studies a flexible class of the semiparametric Cox-Aalen transformation models...
Tianyu Zhang,Noah Simon
Tianyu Zhang
Estimation of a conditional mean (linking a set of features to an outcome of interest) is a fundamental statistical task. While there is an appeal to flexible nonparametric procedures, effective estimation in many classical nonparametric fu...
Robust improvement of efficiency using information on covariate distribution [0.03%]
利用协变量分布信息改进估计效率的稳健方法
Lu Mao
Lu Mao
The marginal inference of an outcome variable can be improved by closely related covariates with a structured distribution. This differs from standard covariate adjustment in randomized trials, which exploits covariate-treatment independenc...
Bohao Tang,Sandipan Pramanik,Yi Zhao et al.
Bohao Tang et al.
In this manuscript, we study scalar-on-distribution regression; that is, instances where subject-specific distributions or densities are the covariates, related to a scalar outcome via a regression model. In practice, only repeated measures...
Online inference in high-dimensional generalized linear models with streaming data [0.03%]
在线高维广义线性模型的流数据推理
Lan Luo,Ruijian Han,Yuanyuan Lin et al.
Lan Luo et al.
In this paper we develop an online statistical inference approach for high-dimensional generalized linear models with streaming data for realtime estimation and inference. We propose an online debiased lasso method that aligns with the data...
Testing Linear Operator Constraints in Functional Response Regression with Incomplete Response Functions [0.03%]
带有不完整响应函数的功能性响应回归中的线性算子约束检验
Yeonjoo Park,Kyunghee Han,Douglas G Simpson
Yeonjoo Park
Hypothesis testing procedures are developed to assess linear operator constraints in function-on-scalar regression when incomplete functional responses are observed. The approach enables statistical inferences about the shape and other aspe...
Estimating causal effects with hidden confounding using instrumental variables and environments [0.03%]
使用仪器变量和环境隐匿混淆因素估计因果效应
James P Long,Hongxu Zhu,Kim-Anh Do et al.
James P Long et al.
Recent works have proposed regression models which are invariant across data collection environments [24, 20, 11, 16, 8]. These estimators often have a causal interpretation under conditions on the environments and type of invariance impose...
Adversarial meta-learning of Gamma-minimax estimators that leverage prior knowledge [0.03%]
利用先验知识的Gamma-极小极大估计器的对抗元学习
Hongxiang Qiu,Alex Luedtke
Hongxiang Qiu
Bayes estimators are well known to provide a means to incorporate prior knowledge that can be expressed in terms of a single prior distribution. However, when this knowledge is too vague to express with a single prior, an alternative approa...