2025

最新文章

• Dynamic Regression of Longitudinal Trajectory Features AI翻译
  作者：Ma, Huijuan; Zhao, Wei; Hanfelt, John; Peng, Limin
  作者单位：East China Normal University; Shandong University; Emory University; Rollins School Public Health
  摘要：Chronic disease studies often collect data on biological and clinical markers at follow-up visits to monitor disease progression. Viewing such longitudinal measurements governed by latent continuous trajectories, we develop a new dynamic regression framework to investigate the heterogeneity pattern of certain features of the latent individual trajectory that may carry substantive information on disease risk or status. Employing the strategy of multi-level modeling, we formulate the latent indi...
• Class-Specific Joint Feature Screening in Ultrahigh-Dimensional Mixture Regression AI翻译
  作者：Jing, Kaili; Khalili, Abbas; Xu, Chen
  作者单位：Xi'an Jiaotong University; McGill University; Peng Cheng Laboratory
  摘要：Finite mixture of regression models are ubiquitous for analyzing complex data. They aim to detect heterogeneity in the effects of a set of features on a response over a finite number of latent classes. When the number of features is large, a direct fitting of mixture regressions can be computationally infeasible and often leads to a poor interpretative value. One practical strategy is to screen out most irrelevant features before an in-depth analysis. In this article, we propose a novel method...
• Estimation and Variable Selection for Interval-Censored Failure Time Data with Random Change Point and Application to Breast Cancer Study AI翻译
  作者：Du, Mingyue; Lou, Yichen; Sun, Jianguo
  作者单位：Jilin University; Chinese University of Hong Kong; University of Missouri System; University of Missouri Columbia
  摘要：Motivated by a breast cancer study, we consider regression analysis of interval-censored failure time data in the presence of a random change point. Although a great deal of literature on interval-censored data has been established, there does not seem to exist an established method that can allow for the existence of random change points. Such data can occur in, for example, clinical trials where the risk of a disease may dramatically change when some biological indexes of the human body exce...
• Debiasing Watermarks for Large Language Models via Maximal Coupling AI翻译
  作者：Xie, Yangxinyu; Li, Xiang; Mallick, Tanwi; Su, Weijie; Zhang, Ruixun
  作者单位：University of Pennsylvania; University of Pennsylvania; Pennsylvania Medicine; United States Department of Energy (DOE); Argonne National Laboratory; Peking University; Peking University; University of Oxford; University of Oxford
  摘要：Watermarking language models is essential for distinguishing between human and machine-generated text and thus maintaining the integrity and trustworthiness of digital communication. We present a novel green/red list watermarking approach that partitions the token set into green and red lists, subtly increasing the generation probability for green tokens. To correct token distribution bias, our method employs maximal coupling, using a uniform coin flip to decide whether to apply bias correctio...
• Manipulating an Instrumental Variable in an Observational Study of Premature Babies: Design, Bounds, and Inference AI翻译
  作者：Chen, Zhe; Cho, Min Haeng; Zhang, Bo
  作者单位：University of Pennsylvania; Pennsylvania Medicine; University of Washington; University of Washington Seattle; Fred Hutchinson Cancer Center
  摘要：Regionalization of intensive care for premature infants refers to a triage system that directs mothers to hospitals with varying capabilities based on the risks their babies face. Given the limited capacity of highly specialized hospitals, understanding the impact of delivering premature infants at these facilities on infant mortality could facilitate the design of a more efficient perinatal regionalization system. To address this, Baiocchi et al. proposed strengthening a continuous instrument...
• Adaptation Using Spatially Distributed Gaussian Processes AI翻译
  作者：Szabo, Botond; Hadji, Amine; van der Vaart, Aad
  作者单位：Bocconi University; Bocconi University; Leiden University - Excl LUMC; Leiden University; Delft University of Technology
  摘要：We consider the accuracy of an approximate posterior distribution in nonparametric regression problems by combining posterior distributions computed on subsets of the data defined by the locations of the independent variables. We show that this approximate posterior retains the rate of recovery of the full data posterior distribution, where the rate of recovery adapts to the smoothness of the true regression function. As particular examples we consider Gaussian process priors based on integrat...
• Analyzing Whale Calling through Hawkes Process Modeling AI翻译
  作者：Kang, Bokgyeong; Schliep, Erin M.; Gelfand, Alan E.; Yack, Tina M.; Clark, Christopher W.; Schick, Robert S.
  作者单位：Duke University; Dongguk University; North Carolina State University; Duke University; Cornell University
  摘要：Sound is assumed to be the primary modality of communication among marine mammal species. Analyzing acoustic recordings helps to understand the function of the acoustic signals as well as the possible impact of anthropogenic noise on acoustic behavior. Motivated by a dataset from a network of hydrophones in Cape Cod Bay, Massachusetts, using automatically detected calls in recordings, we study the communication process of the endangered North Atlantic right whale. For right whales, an upcall i...
• Simultaneous Inference for Generalized Linear Models with Unmeasured Confounders AI翻译
  作者：Du, Jin-Hong; Wasserman, Larry; Roeder, Kathryn
  作者单位：Carnegie Mellon University; Carnegie Mellon University; Carnegie Mellon University
  摘要：Tens of thousands of simultaneous hypothesis tests are routinely performed in genomic studies to identify differentially expressed genes. However, due to unmeasured confounders, many standard statistical approaches may be substantially biased. This article investigates the large-scale hypothesis testing problem for multivariate generalized linear models in the presence of confounding effects. Under arbitrary confounding mechanisms, we propose a unified statistical estimation and inference fram...
• Prediction of Cognitive Function via Brain Region Volumes with Applications to Alzheimer's Disease Based on Space-Factor-Guided Functional Principal Component Analysis AI翻译
  作者：Wen, Shoudao; Li, Yi; Kong, Dehan; Lin, Huazhen
  作者单位：Southwestern University of Finance & Economics - China; Southwestern University of Finance & Economics - China; University of Michigan System; University of Michigan; University of Toronto
  摘要：Alzheimer's disease (AD) is a prevalent and irreversible brain disorder and early prediction of cognitive function is vital for detecting the onset. The volumes of brain regions can serve as features for predicting cognitive decline, facilitating early detection and intervention. In order to offer a comprehensive representation of brain tissue changes in AD, we employ volume density curves to investigate the relationship between brain regions and cognitive function. However, analyzing these vo...
• Frequency Domain Statistical Inference for High-Dimensional Time Series AI翻译
  作者：Krampe, Jonas; Paparoditis, Efstathios
  作者单位：Cornell University; University of Cyprus
  摘要：Analyzing time series in the frequency domain enables the development of powerful tools for investigating the second-order characteristics of multivariate processes. Parameters like the spectral density matrix and its inverse, the coherence or the partial coherence, encode comprehensively the complex linear relations between the component processes of the multivariate system. In this article, we develop inference procedures for such parameters in a high-dimensional, time series setup. Toward t...