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作者：Englert, Jacob R.; Ebelt, Stefanie T.; Chang, Howard H.
作者单位：Emory University; Rollins School Public Health; Emory University
摘要：Epidemiological approaches for examining human health responses to environmental exposures in observational studies often control for confounding by implementing clever matching schemes and using statistical methods based on conditional likelihood. Nonparametric regression models have surged in popularity in recent years as a tool for estimating individual-level heterogeneous effects, which provide a more detailed picture of the exposure-response relationship but can also be aggregated to obta...
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作者：Ghosal, Rahul; Ghosh, Sujit K.; Schrack, Jennifer A.; Zipunnikov, Vadim
作者单位：University of South Carolina System; University of South Carolina Columbia; North Carolina State University; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health
摘要：Modern clinical and epidemiological studies widely employ wearables to record parallel streams of real-time data on human physiology and behavior. With recent advances in distributional data analysis, these high-frequency data are now often treated as distributional observations resulting in novel regression settings. Motivated by these modeling setups, we develop a distributional outcome regression via quantile functions (DORQF) that expands existing literature with three key contributions: (...
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作者：Hong, Shizhe; Li, Weiming; Liu, Qiang; Zhang, Yangchun
作者单位：Shanghai University of Finance & Economics; Shanghai University
摘要：The R-2 statistic and its classic adjusted version, say R-& lowast;2 , tend to overestimate the multiple correlation coefficient when dealing with multivariate data that exhibit heavy tails and tail dependence. This can result in an incorrect significance of correlation in high-dimensional scenarios. A new adaptive adjustment to the R-2 statistic is proposed in this article, which applies to a general population model that covers the family of elliptical distributions and an independent compon...
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作者：Yao, Zeyu; Sun, Wenguang; Gang, Bowen
作者单位：Zhejiang University; Zhejiang University; Zhejiang University; Zhejiang University; Fudan University
摘要：Dynamic decision-making in rapidly evolving research domains, including marketing, finance, and pharmaceutical development, presents a significant challenge. Researchers frequently confront the need for real-time action within a doubly sequential framework characterized by the continuous influx of high-volume data streams and the intermittent arrival of novel tasks. This calls for the development and implementation of new online inference protocols capable of handling both the continuous proce...
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作者：Dharmakeerthi, Kulunu; Hur, YoonHaeng; Liang, Tengyuan
作者单位：University of Chicago; University of Chicago
摘要：Practitioners often face the challenge of deploying prediction models in new environments with shifted distributions of covariates and responses. With observational data, such shifts are often driven by unobserved confounding, and can in fact alter the concept of which model is best. This article studies distribution shifts in the domain adaptation problem with unobserved confounding. We postulate a linear structural causal model to account for endogeneity and unobserved confounding, and we le...
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作者：Meng, Xiao-Li
作者单位：Harvard University
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作者：Hingee, Kassel L.; Scealy, Janice L.; Wood, Andrew T. A.
作者单位：Australian National University
摘要：Symmetric matrices (tensors) are measured in geophysics and other disciplines, including in medical imaging, and typically their eigenvalues have valuable scientific interpretations. We design pivotal bootstrap hypothesis tests of specified eigenvalues or eigenvalue multiplicities in one-sample situations and for equal eigenvalues in k-sample situations. Our tests are more broadly applicable than existing tests by allowing very general distributions, allowing three or more samples, and account...
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作者：Xie, Zhongming; Zhang, Wanheng; Wang, Jingshen; Wu, Chong
作者单位：University of California System; University of California Berkeley; University of Texas System; UTMD Anderson Cancer Center
摘要：In the past decade, the increased availability of genome-wide association studies summary data has popularized Mendelian Randomization (MR) for conducting causal inference. MR analyses, incorporating genetic variants as instrumental variables, are known for their robustness against reverse causation bias and unmeasured confounders. Nevertheless, classical MR analyses using summary data may still produce biased causal effect estimates due to the winner's curse and pleiotropy issues. To address ...
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作者：Song, Difan; Lewis, William E.; Knapp, Patrick F.; Wu, C. F. Jeff; Joseph, V. Roshan
作者单位：University System of Georgia; Georgia Institute of Technology; United States Department of Energy (DOE); Sandia National Laboratories
摘要：The configurations of instruments fielded on an experiment affect the amount of information captured and the quality of subsequent inference. We investigate the problem of optimizing plasma x-ray radiation detectors in a magneto-inertial fusion experiment at Sandia National Laboratories. It is impossible to directly measure properties such as the temperature of the thermonuclear fusion plasma produced in these experiments because of the extreme environment and destructive nature of the experim...
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作者：Luo, Tianpai; Wu, Weichi
作者单位：Tsinghua University
摘要：We propose a new framework for the simultaneous inference of monotone and smoothly time-varying functions under complex temporal dynamics. This will be done using the monotone rearrangement and the nonparametric estimation. We capitalize the Gaussian approximation for the nonparametric monotone estimator and construct the asymptotically correct simultaneous confidence bands (SCBs) using designed bootstrap methods. We investigate two general and practical scenarios. The first is the simultaneou...
