The Annals of Applied Statistics

最新文章

• A DYNAMIC SCREENING ALGORITHM FOR HIERARCHICAL BINARY MARKETING DATA AI翻译
  作者：Fan, Yimei; Liao, Yuan; Ryzhov, Ilya o.; Zhang, Kunpeng
  作者单位：University System of Maryland; University of Maryland College Park; Rutgers University System; Rutgers University New Brunswick; Rutgers University Newark; University System of Maryland; University of Maryland College Park
  摘要：In many applications of business and marketing analytics, predictive models are fit using hierarchically structured data: common characteristics of products, customers, or web pages are represented as categorical variables, and each category can be split up into multiple subcategories at a lower level of the hierarchy. The model may thus contain hundreds of thousands of binary variables, necessitating the use of variable selection to screen out large numbers of irrelevant or insignificant feat...
• TRUNCATED RANK-BASED TESTS FOR TWO-PART MODELS WITH EXCESSIVE ZEROS AND APPLICATIONS TO MICROBIOME DATA AI翻译
  作者：Wang, Wanjie; Chen, Eric; Li, Hongzhe
  作者单位：National University of Singapore; University of Pennsylvania
  摘要：High-throughput sequencing technology allows us to test the composi-tional difference of bacteria in different populations. One important feature of human microbiome data is that it often includes a large number of ze-ros. Such data can be treated as being generated from a two-part model that includes a zero-point mass. Motivated by analysis of such nonnegative data with excessive zeros, we introduce several truncated rank-based two-group and multigroup tests, including a truncated rank-based ...
• BAYESIAN CLASSIFICATION, ANOMALY DETECTION, AND SURVIVAL ANALYSIS USING NETWORK INPUTS WITH APPLICATION TO THE AI翻译
  作者：Josephs, Nathaniel; Lin, Lizhen; Rosenberg, Steven; Kolaczyk, Eric D.
  作者单位：Yale University; University of Notre Dame; Boston University
  摘要：While the study of a single network is well established, technological advances now allow for the collection of multiple networks with relative ease. Increasingly, anywhere from several to thousands of networks can be created from brain imaging, gene coexpression data, or microbiome measurements. And these networks, in turn, are being looked to as potentially powerful features to be used in modeling. However, with networks being non-Euclidean in nature, how best to incorporate them into standa...
• SPATIOTEMPORAL WILDFIRE MODELING THROUGH POINT PROCESSES WITH MODERATE AND EXTREME MARKS AI翻译
  作者：Koh, Jonathan; Pimont, Francois; Dupuy, Jean-Luc; Opitz, Thomas
  作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University of Bern; INRAE; INRAE
  摘要：Accurate spatiotemporal modeling of conditions leading to moderate and large wildfires provides better understanding of mechanisms driving fireprone ecosystems and improves risk management. Here, we develop a joint model for the occurrence intensity and the wildfire size distribution, by combining extreme-value theory and point processes within a novel Bayesian hierarchical model, and use it to study daily summer wildfire data for the French Mediterranean basin during 1995-2018. The occurrence...
• DYNAMIC PREDICTION OF RESIDUAL LIFE WITH LONGITUDINAL COVARIATES USING LONG SHORT-TERM MEMORY NETWORKS AI翻译
  作者：Rhodes, Grace; Davidian, Marie; Lu, Wenbin
  作者单位：North Carolina State University
  摘要：Sepsis, a complex medical condition that involves severe infections with life-threatening organ dysfunction, is a leading cause of death worldwide. Treatment of sepsis is highly challenging. When making treatment decisions, clinicians and patients desire accurate predictions of mean residual life (MRL) that leverage all available patient information, including longitudinal biomarker data. Biomarkers are biological, clinical, and other variables reflecting disease progression that are often mea...
• SPATIOTEMPORAL LOCAL INTERPOLATION OF GLOBAL OCEAN HEAT TRANSPORT USING ARGO FLOATS: A DEBIASED LATENT GAUSSIAN PROCESS APPROACH AI翻译
  作者：Park, Beomjo; Kuusela, Mikael; Giglio, Donata; Gray, Alison
  作者单位：Carnegie Mellon University; University of Colorado System; University of Colorado Boulder; University of Washington; University of Washington Seattle
  摘要：The world ocean plays a key role in redistributing heat in the climate system and hence in regulating Earth's climate. Yet statistical analysis of ocean heat transport suffers from partially incomplete large-scale data intertwined with complex spatiotemporal dynamics as well as from potential model misspecification. We present a comprehensive spatiotemporal statistical framework tailored to interpolating the global ocean heat transport using in situ Argo profiling float measurements. We formal...
• MODELING PANELS OF EXTREMES AI翻译
  作者：Dupuis, Debbie J.; Engelke, Sebastian; Trapin, Luca
  作者单位：Universite de Montreal; HEC Montreal; University of Geneva; University of Bologna
  摘要：Extreme value applications commonly employ regression techniques to capture cross-sectional heterogeneity or time variation in the data. Estimation of the parameters of an extreme value regression model is notoriously challenging due to the small number of observations that are usually available in applications. When repeated extreme measurements are collected on the same individuals, that is, a panel of extremes is available, pooling the observations in groups can improve the statistical infe...
• CONTROL CHARTS FOR DYNAMIC PROCESS MONITORING WITH AN APPLICATION TO AIR POLLUTION SURVEILLANCE AI翻译
  作者：Xie, Xiulin; Qiu, Peihua
  作者单位：State University System of Florida; University of Florida
  摘要：Air pollution is a major global public health risk factor. Among all air pollutants, PM2.5 is especially harmful. It has been well demonstrated that chronic exposure to PM2.5 can cause many health problems, including asthma, lung cancer and cardiovascular diseases. To tackle problems caused by air pollution, governments have put a huge amount of resources to improve air quality and reduce the impact of air pollution on public health. In this effort it is extremely important to develop an air p...
• BAYESIAN HIERARCHICAL MODELING AND ANALYSIS FOR ACTIGRAPH DATA FROM WEARABLE DEVICES AI翻译
  作者：Di Loro, Pierfrancesco Alaimo; Mingione, Marco; Lipsitt, Jonah; Batteate, Christina M.; Jerrett, Michael; Banerjee, Sudipto
  作者单位：Universita LUMSA; Roma Tre University; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles
  摘要：The majority of Americans fail to achieve recommended levels of physical activity, which leads to numerous preventable health problems, such as diabetes, hypertension, and heart diseases. This has generated substantial interest in monitoring human activity to gear interventions toward environmental features that may relate to higher physical activity. Wearable devices, such as wrist-worn sensors that monitor gross motor activity (actigraph units) continuously record the activity levels of a su...
• A BAYESIAN DECISION FRAMEWORK FOR OPTIMIZING SEQUENTIAL COMBINATION ANTIRETROVIRAL THERAPY IN PEOPLE WITH HIV AI翻译
  作者：Jin, Wei; Ni, Yang; O'Halloran, Jane; Spence, Amanda B.; Rubin, Leah H.; Xu, Yanxun
  作者单位：Johns Hopkins University; Texas A&M University System; Texas A&M University College Station; Washington University (WUSTL); Georgetown University; Johns Hopkins University; Johns Hopkins University
  摘要：Numerous adverse effects (e.g., depression) have been reported for combination antiretroviral therapy (cART) despite its remarkable success in viral suppression in people with HIV (PWH). To improve long-term health outcomes for PWH, there is an urgent need to design personalized optimal cART with the lowest risk of comorbidity in the emerging field of precision medicine for HIV. Large-scale HIV studies offer researchers unprecedented opportunities to optimize personalized cART in a data-driven...