540期

最新文章

• Inference of Breakpoints in High-dimensional Time Series AI翻译
  作者：Chen, Likai; Wang, Weining; Wu, Wei Biao
  作者单位：Washington University (WUSTL); University of Chicago
  摘要：For multiple change-points detection of high-dimensional time series, we provide asymptotic theory concerning the consistency and the asymptotic distribution of the breakpoint statistics and estimated break sizes. The theory backs up a simple two-step procedure for detecting and estimating multiple change-points. The proposed two-step procedure involves the maximum of a MOSUM (moving sum) type statistics in the first step and a CUSUM (cumulative sum) refinement step on an aggregated time serie...
• Mapping the Genetic-Imaging-Clinical Pathway with Applications to Alzheimer's Disease AI翻译
  作者：Yu, Dengdeng; Wang, Linbo; Kong, Dehan; Zhu, Hongtu
  作者单位：University of Texas System; University of Texas Arlington; University of Toronto; University of North Carolina; University of North Carolina Chapel Hill
  摘要：Alzheimer's disease is a progressive form of dementia that results in problems with memory, thinking, and behavior. It often starts with abnormal aggregation and deposition of beta amyloid and tau, followed by neuronal damage such as atrophy of the hippocampi, leading to Alzheimer's disease (AD). The aim of this article is to map the genetic-imaging-clinical pathway for AD in order to delineate the genetically-regulated brain changes that drive disease progression based on the Alzheimer's Dise...
• Sampling: Design and Analysis, 3rd ed. AI翻译
  作者：Stokes, S. Lynne
  作者单位：Southern Methodist University
• Testing Independence Under Biased Sampling AI翻译
  作者：Tenzer, Yaniv; Mandel, Micha; Zuk, Or
  作者单位：Hebrew University of Jerusalem; Weizmann Institute of Science
  摘要：Testing for dependence between pairs of random variables is a fundamental problem in statistics. In some applications, data are subject to selection bias that can create spurious dependence. An important example is truncation models, in which observed pairs are restricted to a specific subset of the X-Y plane. Standard tests for independence are not suitable in such cases, and alternative tests that take the selection bias into account are required. Here, we generalize the notion of quasi-inde...
• Heterogeneous Mediation Analysis on Epigenomic PTSD and Traumatic Stress in a Predominantly African American Cohort AI翻译
  作者：Xue, Fei; Tang, Xiwei; Kim, Grace; Koenen, Karestan C.; Martin, Chantel L.; Galea, Sandro; Wildman, Derek; Uddin, Monica; Qu, Annie
  作者单位：Purdue University System; Purdue University; University of Virginia; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Harvard University; Harvard T.H. Chan School of Public Health; University of North Carolina; University of North Carolina Chapel Hill; Boston University; State University System of Florida; University of South Florida; University of California System; University of California Irvine
  摘要：DNA methylation (DNAm) has been suggested to play a critical role in post-traumatic stress disorder (PTSD), through mediating the relationship between trauma and PTSD. However, this underlying mechanism of PTSD for African Americans still remains unknown. To fill this gap, in this article, we investigate how DNAm mediates the effects of traumatic experiences on PTSD symptoms in the Detroit Neighborhood Health Study (DNHS) (2008-2013) which involves primarily African Americans adults. To achiev...
• Modeling Time-Varying Random Objects and Dynamic Networks AI翻译
  作者：Dubey, Paromita; Muller, Hans-Georg
  作者单位：Stanford University; University of California System; University of California Davis
  摘要：Samples of dynamic or time-varying networks and other random object data such as time-varying probability distributions are increasingly encountered in modern data analysis. Common methods for time-varying data such as functional data analysis are infeasible when observations are time courses of networks or other complex non-Euclidean random objects that are elements of general metric spaces. In such spaces, only pairwise distances between the data objects are available and a strong limitation...
• Robust Two-Step Wavelet-Based Inference for Time Series Models AI翻译
  作者：Guerrier, Stephane; Molinari, Roberto; Victoria-Feser, Maria-Pia; Xu, Haotian
  作者单位：University of Geneva; Auburn University System; Auburn University
  摘要：Latent time series models such as (the independent sum of) ARMA(p, q) models with additional stochastic processes are increasingly used for data analysis in biology, ecology, engineering, and economics. Inference on and/or prediction from these models can be highly challenging: (i) the data may contain outliers that can adversely affect the estimation procedure; (ii) the computational complexity can become prohibitive when the time series are extremely large; (iii) model selection adds another...
• Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse, and Fragmented Functional Data AI翻译
  作者：Matuk, James; Bharath, Karthik; Chkrebtii, Oksana; Kurtek, Sebastian
  作者单位：University System of Ohio; Ohio State University; University of Nottingham
  摘要：In many applications, smooth processes generate data that are recorded under a variety of observational regimes, including dense sampling and sparse or fragmented observations that are often contaminated with error. The statistical goal of registering and estimating the individual underlying functions from discrete observations has thus far been mainly approached sequentially without formal uncertainty propagation, or in an application-specific manner by pooling information across subjects. We...
• Nonparametric Fusion Learning for Multiparameters: Synthesize Inferences From Diverse Sources Using Data Depth and Confidence Distribution AI翻译
  作者：Liu, Dungang; Liu, Regina Y.; Xie, Min-ge
  作者单位：University System of Ohio; University of Cincinnati; Rutgers University System; Rutgers University New Brunswick
  摘要：Fusion learning refers to synthesizing inferences from multiple sources or studies to make a more effective inference and prediction than from any individual source or study alone. Most existing methods for synthesizing inferences rely on parametric model assumptions, such as normality, which often do not hold in practice. We propose a general nonparametric fusion learning framework for synthesizing inferences for multiparameters from different studies. The main tool underlying the proposed fr...
• Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise AI翻译
  作者：Romano, Gaetano; Rigaill, Guillem; Runge, Vincent; Fearnhead, Paul
  作者单位：Lancaster University; Universite Paris Saclay; Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); INRAE; Centre National de la Recherche Scientifique (CNRS); Universite Paris Saclay
  摘要：While there are a plethora of algorithms for detecting changes in mean in univariate time-series, almost all struggle in real applications where there is autocorrelated noise or where the mean fluctuates locally between the abrupt changes that one wishes to detect. In these cases, default implementations, which are often based on assumptions of a constant mean between changes and independent noise, can lead to substantial over-estimation of the number of changes. We propose a principled approa...