545期

最新文章

• Bias-Correction and Test for Mark-Point Dependence with Replicated Marked Point Processes AI翻译
  作者：Xu, Ganggang; Zhang, Jingfei; Li, Yehua; Guan, Yongtao
  作者单位：University of Miami; University of California System; University of California Riverside
  摘要：Mark-point dependence plays a critical role in research problems that can be fitted into the general framework of marked point processes. In this work, we focus on adjusting for mark-point dependence when estimating the mean and covariance functions of the mark process, given independent replicates of the marked point process. We assume that the mark process is a Gaussian process and the point process is a log-Gaussian Cox process, where the mark-point dependence is generated through the depen...
• Bootstrapping Extreme Value Estimators AI翻译
  作者：de Haan, Laurens; Zhou, Chen
  作者单位：Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; Universidade de Lisboa; Tinbergen Institute
  摘要：This article develops a bootstrap analogue of the well-known asymptotic expansion of the tail quantile process in extreme value theory. One application of this result is to construct confidence intervals for estimators of the extreme value index such as the Probability Weighted Moment (PWM) estimator. For the peaks-over-threshold method, we show the bootstrap consistency of the confidence intervals. By contrast, the asymptotic expansion of the quantile process of the bootstrapped block maxima ...
• Modeling and Active Learning for Experiments with Quantitative-Sequence Factors AI翻译
  作者：Xiao, Qian; Wang, Yaping; Mandal, Abhyuday; Deng, Xinwei
  作者单位：University System of Georgia; University of Georgia; East China Normal University; Virginia Polytechnic Institute & State University
  摘要：A new type of experiment that aims to determine the optimal quantities of a sequence of factors is eliciting considerable attention in medical science, bioengineering, and many other disciplines. Such studies require the simultaneous optimization of both quantities and the sequence orders of several components which are called quantitative-sequence (QS) factors. Given the large and semi-discrete solution spaces in such experiments, efficiently identifying optimal or near-optimal solutions by u...
• Randomization-based Joint Central Limit Theorem and Efficient Covariate Adjustment in Randomized Block 2K Factorial Experiments AI翻译
  作者：Liu, Hanzhong; Ren, Jiyang; Yang, Yuehan
  作者单位：Tsinghua University; Central University of Finance & Economics
  摘要：Randomized block factorial experiments are widely used in industrial engineering, clinical trials, and social science. Researchers often use a linear model and analysis of covariance to analyze experimental results; however, limited studies have addressed the validity and robustness of the resulting inferences because assumptions for a linear model might not be justified by randomization in randomized block factorial experiments. In this article, we establish a new finite population joint cent...
• A New and Unified Family of Covariate Adaptive Randomization Procedures and Their Properties AI翻译
  作者：Ma, Wei; Li, Ping; Zhang, Li-Xin; Hu, Feifang
  作者单位：Renmin University of China; Zhejiang University; Zhejiang University; George Washington University
  摘要：In clinical trials and other comparative studies, covariate balance is crucial for credible and efficient assessment of treatment effects. Covariate adaptive randomization (CAR) procedures are extensively used to reduce the likelihood of covariate imbalances occurring. In the literature, most studies have focused on balancing of discrete covariates. Applications of CAR with continuous covariates remain rare, especially when the interest goes beyond balancing only the first moment. In this arti...
• Recommender Systems: A Review AI翻译
  作者：LeBlanc, Patrick M.; Banks, David; Fu, Linhui; Li, Mingyan; Tang, Zhengyu; Wu, Qiuyi
  作者单位：Duke University; University of North Carolina; University of North Carolina Greensboro; University of Rochester
  摘要：Recommender systems are the engine of online advertising. Not only do they suggest movies, music, or romantic partners, but they also are used to select which advertisements to show to users. This paper reviews the basics of recommender system methodology and then looks at the emerging arena of active recommender systems.
• Robust Inference and Modeling of Mean and Dispersion for Generalized Linear Models AI翻译
  作者：Ponnet, Jolien; Segaert, Pieter; Van Aelst, Stefan; Verdonck, Tim
  作者单位：KU Leuven; University of Antwerp; University of Antwerp
  摘要：Generalized Linear Models (GLMs) are a popular class of regression models when the responses follow a distribution in the exponential family. In real data the variability often deviates from the relation imposed by the exponential family distribution, which results in over- or underdispersion. Dispersion effects may even vary in the data. Such datasets do not follow the traditional GLM distributional assumptions, leading to unreliable inference. Therefore, the family of double exponential dist...
• Estimating Optimal Infinite Horizon Dynamic Treatment Regimes via pT-Learning AI翻译
  作者：Zhou, Wenzhuo; Zhu, Ruoqing; Qu, Annie
  作者单位：University of California System; University of California Irvine; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：Recent advances in mobile health (mHealth) technology provide an effective way to monitor individuals' health statuses and deliver just-in-time personalized interventions. However, the practical use of mHealth technology raises unique challenges to existing methodologies on learning an optimal dynamic treatment regime. Many mHealth applications involve decision-making with large numbers of intervention options and under an infinite time horizon setting where the number of decision stages diver...
• An Empirical Bares Approach to Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices AI翻译
  作者：Yang, Chun-Hao; Doss, Hani; Vemuri, Baba C.
  作者单位：National Taiwan University; State University System of Florida; University of Florida; State University System of Florida; University of Florida
  摘要：The James-Stein estimator is an estimator of the multivariate normal mean and dominates likelihood estimator (MLE) under squared error loss. The original work inspired great interest in developing shrinkage estimators for a variety of problems. Nonetheless, research on shrinkage estimation for manifold- valued data is scarce. In this article, we propose shrinkage estimators for the parameters of the Log-Normal distribution defined on the manifold of N x N symmetric positive-definite matrices. ...
• Overcoming Repeated Testing Schedule Bias in Estimates of Disease Prevalence AI翻译
  作者：Schnell, Patrick M.; Wascher, Matthew; Rempala, Grzegorz A.
  作者单位：University System of Ohio; Ohio State University; University System of Ohio; University of Dayton
  摘要：During the COVID-19 pandemic, many institutions such as universities and workplaces implemented testing regimens with every member of some population tested longitudinally, and those testing positive isolated for some time. Although the primary purpose of such regimens was to suppress disease spread by identifying and isolating infectious individuals, testing results were often also used to obtain prevalence and incidence estimates. Such estimates are helpful in risk assessment and institution...