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作者：Han, Yang; Wu, Weichi; Zhang, Wenyang
作者单位：University of Manchester; Tsinghua University
摘要：In panel data analysis, individual attributes are of importance in many real applications. With the advancement of data collection, it is often possible to acquire enough information for individual attributes in a collected panel dataset, and data from other individuals may contain the information for the attributes of the individual under concern. Homogeneity pursuit is an important topic in panel data analysis when individual attributes are of interest. Existing approaches are mainly based o...
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作者：Kirch, Claudia; Klein, Philipp; Meyer, Marco
作者单位：Otto von Guericke University; Leibniz University Hannover
摘要：Anomaly detection in random fields is an important problem in many applications including the detection of cancerous cells in medicine, obstacles in autonomous driving and cracks in the construction material of buildings. Such anomalies are often visible as areas with different expected values compared to the background noise. Scan statistics based on local means have the potential to detect such local anomalies by enhancing relevant features. We derive limit theorems for a general class of su...
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作者：Fritz, Cornelius; Schweinberger, Michael; Bhadra, Subhankar; Hunter, David R.
作者单位：Trinity College Dublin; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：To understand how the interconnected and interdependent world of the twenty-first century operates and make model-based predictions, joint probability models for networks and interdependent outcomes are needed. We propose a comprehensive regression framework for networks and interdependent outcomes with multiple advantages, including interpretability, scalability, and provable theoretical guarantees. The regression framework can be used for studying relationships among attributes of connected ...
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作者：Zhang, Lu; Tang, Wenpin; Banerjee, Sudipto
作者单位：University of Southern California; Columbia University; University of California System; University of California Los Angeles
摘要：We develop Bayesian predictive stacking for geostatistical models, where the primary inferential objective is to provide inference on the latent spatial random field and conduct spatial predictions at arbitrary locations. We exploit analytically tractable posterior distributions for regression coefficients of predictors and the realizations of the spatial process conditional upon process parameters. We subsequently combine such inference by stacking these models across the range of values of t...
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作者：Yang, Jingyuan; Li, Tao; Wang, Tianyi; Ma, Shuangge; Wu, Mengyun
作者单位：Yale University
摘要：Estimation of intracellular gene networks has been a critical component of single-cell transcriptomic data analysis, which can provide crucial insights into the complex interplay between genes, facilitating the discovery of the biological basis of human life at single-cell resolution. Despite notable achievements, existing methodologies often falter in their practicality, primarily due to their narrow focus on simplistic linear relationships and inadequate handling of cellular heterogeneity. T...
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作者：Lee, Seong-ho; Richardson, Brian D.; Ma, Yanyuan; Marder, Karen S.; Garcia, Tanya P.
作者单位：University of Seoul; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Columbia University; Cornell University; Weill Cornell Medicine; NewYork-Presbyterian Hospital
摘要：In Huntington disease research, a current goal is to understand how symptoms change prior to a clinical diagnosis. Statistically, achieving this goal entails modeling symptom severity as a function of the covariate time of diagnosis, which is often heavily right-censored in observational studies. Existing estimators that handle right-censored covariates, such as the complete case estimator and maximum likelihood estimator, vary in their statistical efficiency and robustness to misspecification...
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作者：Braunsteins, Peter; Hautphenne, Sophie; Minuesa, Carmen
作者单位：University of New South Wales Sydney; University of Melbourne
摘要：We derive the first conditionally consistent estimators for a class of parametric Markov population models with logistic growth, which are suitable for modeling endangered populations in restricted habitats with a carrying capacity. We focus on discrete-time parametric population-size-dependent branching processes, for which we propose a new class of weighted least-squares estimators based on a single trajectory of population size counts. We establish the consistency and asymptotic normality o...
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作者：Ma, Haiqiang; Nguyen, Thuan; Jiang, Jiming
作者单位：Jiangxi University of Finance & Economics; Oregon Health & Science University; University of California System; University of California Davis
摘要：The mean squared prediction error (MSPE) is widely used in small area estimation (SAE), as well as in other fields of statistics. Despite its popularity, the MSPE is not always practical in that it treats positive error, or over-prediction, and negative error, or under-prediction, equally. In practice, however, the consequences of these two types of errors are often different. This problem has long been known in statistics; however, a practical solution has not received much attention in SAE, ...
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作者：Su, Buxin; Zhang, Jiayao; Collina, Natalie; Yan, Yuling; Li, Didong; Cho, Kyunghyun; Fan, Jianqing; Roth, Aaron; Su, Weijie
作者单位：University of Pennsylvania; University of Pennsylvania; University of Wisconsin System; University of Wisconsin Madison; University of North Carolina; University of North Carolina Chapel Hill; New York University; Princeton University
摘要：We conducted an experiment during the review process of the 2023 International Conference on Machine Learning (ICML), asking authors with multiple submissions to rank their papers based on perceived quality. In total, we received 1342 rankings, each from a different author, covering 2592 submissions. In this article, we present an empirical analysis of how author-provided rankings could be leveraged to improve peer review processes at machine learning conferences. We focus on the Isotonic Mech...
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作者：Haupt, Andreas; Koyejo, Sanmi
作者单位：Stanford University
