553期

最新文章

• PALAR: Estimation of Absolute Abundance Effects in Regression with Relative Abundance Predictors AI翻译
  作者：Li, Yiluan; Wang, Qiyu; Feng, Zekang; Wang, Xueqin; Tang, Zheng-Zheng
  作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; Chinese Academy of Sciences; University of Science & Technology of China, CAS; University of Wisconsin System; University of Wisconsin Madison
  摘要：High-dimensional compositional data are ubiquitous in omics research. Microbiome sequencing experiments measure the relative abundances (proportions) of microbial features, while the absolute abundances within the ecosystem remain unobserved. Most regression methods with microbial relative abundance predictors rely on log-ratio transformations and typically impose sparsity on the regression coefficients to manage high dimensionality. However, we show that the sparsity assumption often does not...
• Inference for Dispersion and Curvature of Random Objects AI翻译
  作者：Song, Wookyeong; Muller, Hans-Georg
  作者单位：University of California System; University of California Davis
  摘要：There are many open questions pertaining to the statistical analysis of random objects, which are increasingly encountered. A major challenge is the absence of linear operations in such spaces. A basic statistical task is to quantify statistical dispersion or spread. For two measures of dispersion for data objects in geodesic metric spaces, Fr & eacute;chet variance and metric variance, we derive a central limit theorem (CLT) for their joint distribution. This analysis reveals that the Alexand...
• Comments: Systems Thinking, Data Minding, and Mindware Agents for Multi-Agent Data Analysis Systems AI翻译
  作者：Meng, Xiao-Li
  作者单位：Harvard University
• SMART-MC: Characterizing the Dynamics of Multiple Sclerosis Therapy Transitions Using a Covariate-Based Markov Model AI翻译
  作者：Kim, Beomchang; Xia, Zongqi; Das, Priyam
  作者单位：Virginia Commonwealth University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Harvard University; Harvard Medical School
  摘要：Treatment switching is a common occurrence in the management of Multiple Sclerosis (MS), where patients transition across various disease-modifying therapies (DMTs) due to heterogeneous treatment responses, differences in disease progression, patient characteristics, and therapy-associated adverse effects. To investigate how patient-level covariates influence the likelihood of treatment transitions among DMTs, we adopt a Markovian framework, Sparse Matrix Estimation with Covariate-Based Transi...
• Efficient Optimization of Plasma Radiation Detector Configurations using Imperfect Inference Models AI翻译
  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...
• Causal Inference in Pharmaceutical Statistics AI翻译
  作者：Buchanan, Ashley L.
  作者单位：University of Rhode Island
• Elastic Shape Analysis of Movement Data AI翻译
  作者：Borgert, J. E.; Hannig, Jan; Tucker, J. Derek; Arbeeva, Liubov; Buck, Ashley N.; Golightly, Yvonne M.; Messier, Stephen P.; Nelson, Amanda E.; Marron, J. S.
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; United States Department of Energy (DOE); Sandia National Laboratories; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of Nebraska System; University of Nebraska Medical Center; University of North Carolina; University of North Carolina Chapel Hill; Wake Forest University; University of North Carolina; University of North Carolina Chapel Hill
  摘要：Osteoarthritis (OA) is a highly prevalent degenerative joint disease, and the knee is the most commonly affected joint. Biomechanical factors, particularly forces exerted during walking, are often measured in modern studies of knee joint injury and OA, and understanding the relationship among biomechanics, clinical profiles, and OA has high clinical relevance. Biomechanical forces are typically represented as curves over time, but a standard practice in biomechanics research is to summarize th...
• A Minimax Two-Sample Test for Functional Data via Grothendieck's Divergence AI翻译
  作者：Chen, Yan; Lin, Hongmei; Wang, Xueqin; Wen, Canhong
  作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; Shanghai University of International Business & Economics; Chinese Academy of Sciences; University of Science & Technology of China, CAS
  摘要：Our proposed approach addresses the challenges associated with nonparametric two-sample testing for densely measured functional data. These challenges stem from the high dimensionality of data and the nature of the observation scheme. We introduce a novel metric concept for random functions known as Grothendieck's divergence to overcome these challenges, which satisfies the homogeneity-zero equivalence property. Our approach uses a pre-smoothing technique on densely measured functional data an...
• SOFARI: High-Dimensional Manifold-Based Inference AI翻译
  作者：Zheng, Zemin; Zhou, Xin; Fan, Yingying; Lv, Jinchi
  作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; University of Southern California
  摘要：Multi-task learning is a widely used technique for harnessing information from various tasks. Recently, the sparse orthogonal factor regression (SOFAR) framework, based on the sparse singular value decomposition (SVD) within the coefficient matrix, was introduced for interpretable multi-task learning, enabling the discovery of meaningful latent feature-response association networks across different layers. However, conducting precise inference on the latent factor matrices has remained challen...
• Additive Multi-Index Gaussian Process Modeling, with Application to Multi-Physics Surrogate Modeling of the Quark-Gluon Plasma AI翻译
  作者：Li, Kevin; Mak, Simon; Paquet, J. -F; Bass, Steffen A.
  作者单位：Duke University; Vanderbilt University; Vanderbilt University; Duke University
  摘要：The Quark-Gluon Plasma (QGP) is a unique phase of nuclear matter, theorized to have filled the Universe shortly after the Big Bang. A critical challenge in studying the QGP is that, to reconcile experimental observables with theoretical parameters, one requires many simulation runs of a complex physics model over a high-dimensional parameter space. Each run is computationally expensive, requiring thousands of CPU hours, thus limiting physicists to only several hundred runs. Given limited train...