The Annals of Applied Statistics

最新文章

• ASSESSING MARINE MAMMAL ABUNDANCE: A NOVEL DATA FUSION AI翻译
  作者：Schliep, Erin M.; Gelfand, Alan E.; Clark, Christopher W.; Mayo, Charles A.; Mckenna, Brigid; Parks, Susan E.; Yack, Tina M.; Schick, Roberts.
  作者单位：North Carolina State University; Duke University; Cornell University; Syracuse University; Duke University
  摘要：Marine mammals are increasingly vulnerable to human disturbance and climate change. Their diving behavior leads to limited visual access during data collection, making studying the abundance and distribution of marine mammals challenging. In theory, using data from more than one observation modality should lead to better informed predictions of abundance and distribution. With focus on North Atlantic right whales, we consider the fusion of two data sources to inform about their abundance and d...
• DYNAMIC TOPIC LANGUAGE MODEL ON HETEROGENEOUSCHILDREN'S MENTAL HEALTH CLINICAL NOTES AI翻译
  作者：Ye, Hanwen; Moreno, Tatiana; Alpern, Adrianne; Ehwerhemuepha, Louis; Qu, Annie
  作者单位：University of California System; University of California Irvine; Childrens Hospital of Orange County
  摘要：Mental health diseases which affect children's lives and well-beings havereceived increased attention since the COVID-19 pandemic. Analyzing psy-chiatric clinical notes with topic models is critical to evaluating children'smental status over time. However, few topic models are built for longitudinalsettings, and most existing approaches fail to capture temporal trajectoriesfor each document. To address these challenges, we develop a dynamic topicmodel with consistent topics and individualized ...
• A BOOTSTRAP MODEL COMPARISON TEST FOR IDENTIFYING GENES WITH CONTEXT-SPECIFIC PATTERNS OF GENETIC REGULATION AI翻译
  作者：Malakhov, Mykhaylo M.; Dai, Ben; Shen, Xiaotong T.; Pan, Wei
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Chinese University of Hong Kong; University of Minnesota System; University of Minnesota Twin Cities
  摘要：Understanding how genetic variation affects gene expression is essential for a complete picture of the functional pathways that give rise to complex traits. Although numerous studies have established that many genes are differentially expressed in distinct human tissues and cell types, no tools exist for identifying the genes whose expression is differentially regulated. Here we introduce DRAB (differential regulation analysis by bootstrapping), a gene-based method for testing whether patterns...
• GENERATIVE MACHINE LEARNING METHODS FOR MULTIVARIATE ENSEMBLE POSTPROCESSING AI翻译
  作者：Chen, Jieyu; Janke, Tim; Steinke, Florian; Lerch, Sebastian
  作者单位：Helmholtz Association; Karlsruhe Institute of Technology; Technical University of Darmstadt
  摘要：Ensemble weather forecasts based on multiple runs of numerical weather prediction models typically show systematic errors and require postprocessing to obtain reliable forecasts. Accurately modeling multivariate dependencies is crucial in many practical applications, and various approaches to multivariate postprocessing have been proposed where ensemble predictions are first postprocessed separately in each margin and multivariate dependencies are then restored via copulas. These two-step meth...
• APPLIED REGRESSION ANALYSIS OF CORRELATIONS FOR CORRELATED DATA AI翻译
  作者：Hu, Jie; Chen, Yu; Leng, Chenlei; Tang, Cheng yong
  作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; University of Warwick; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
  摘要：Correlated data are ubiquitous in today's data-driven society. While regression models for analyzing means and variances of responses of interest are relatively well developed, the development of these models for analyzing the correlations is largely confined to longitudinal data, a special form of sequentially correlated data. This paper proposes a new method for the analysis of correlations to fully exploit the use of covariates for general correlated data. In a renewed analysis of the class...
• SUPPORT VECTOR MACHINE FOR DYNAMIC SURVIVAL PREDICTION WITH TIME-DEPENDENT COVARIATES AI翻译
  作者：Xie, Wenyi; Zeng, Donglin; Wang, Yuanjia
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of Michigan System; University of Michigan; Columbia University
  摘要：Predicting time-to-event outcomes using time-dependent covariates is a challenging problem. Many machine learning approaches, such as tree-based methods and support vector regression, predominantly utilize only baseline covariates. Only a few methods can incorporate time-dependent covariates, but they often lack theoretical justification. In this paper we present a new framework for event time prediction, leveraging the support vector machines to forecast the associated counting processes. Uti...
• PATIENT RECRUITMENT USING ELECTRONIC HEALTH RECORDS UNDER SELECTION BIAS: A TWO-PHASE SAMPLING FRAMEWORK AI翻译
  作者：Zhang, Guanghao; Beesley, Lauren j.; Mukherjee, Bhramar; Shi, Xu
  作者单位：University of Michigan System; University of Michigan; United States Department of Energy (DOE); Los Alamos National Laboratory
  摘要：Electronic health records (EHRs) are increasingly recognized as a costeffective resource for patient recruitment in clinical research. However, how to optimally select a cohort from millions of individuals to answer a scientific question of interest remains unclear. Consider a study to estimate the mean or mean difference of an expensive outcome. Inexpensive auxiliary covariates predictive of the outcome may often be available in patients' health records, presenting an opportunity to recruit p...
• FILTRATED COMMON FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS OF MULTIGROUP FUNCTIONAL DATA AI翻译
  作者：Jiao, Shuhao; Frostig, Ron; Ombao, Hernando
  作者单位：City University of Hong Kong; University of California System; University of California Irvine; King Abdullah University of Science & Technology
  摘要：Local field potentials (LFPs) are signals that measure electrical activities in localized cortical regions and are collected from multiple tetrodes implanted across a patch on the surface of cortex. Hence, they can be treated as multigroup functional data, where the trajectories collected across temporal epochs from one tetrode are viewed as a group of functions. In many cases multitetrode LFP trajectories contain both global variation patterns (which are shared by most groups, due to signal s...
• SCALABLE MULTIPLE NETWORK INFERENCE WITH THE JOINT GRAPHICAL HORSESHOE AI翻译
  作者：Lingjaerde, Camilla; Fairfax, Benjamin P.; Richardson, Sylvia; Ruffieux, Helene
  作者单位：MRC Biostatistics Unit; University of Cambridge; University of Oxford
  摘要：Network models are useful tools for modelling complex associations. In statistical omics such models are increasingly popular for identifying and assessing functional relationships and pathways. If a Gaussian graphical model is assumed, conditional independence is determined by the nonzero entries of the inverse covariance (precision) matrix of the data. The Bayesian graphical horseshoe estimator provides a robust and flexible framework for precision matrix inference, as it introduces local, e...
• SPARSE CLUSTERING FOR CUSTOMER SEGMENTATION WITH HIGH-DIMENSIONAL MIXED-TYPE DATA AI翻译
  作者：Wang, Feifei; Xu, Shaodong; Qin, Yichen; Shen, Ye; Li, Yang
  作者单位：Renmin University of China; Renmin University of China; University System of Ohio; University of Cincinnati; University System of Georgia; University of Georgia
  摘要：Customer segmentation has wide applications in business activities, such as personalized marketing and targeted product development. To realize customer segmentation, clustering methods are commonly used. However, modern customer segmentation encounters challenges characterized by highdimensionality and mixed-type variables (i.e., the mixture of continuous variables and categorical variables). It brings great challenges to customer segmentation, because most existing clustering methods are onl...