2025

最新文章

• RICE-DISTRIBUTED AUTOREGRESSIVE TIME SERIES MODELING OF MAGNITUDE FUNCTIONAL MRI DATA AI翻译
  作者：Adrian, Daniel W.; Maitra, Ranjan; Rowe, Daniel B.
  作者单位：Grand Valley State University; Iowa State University; Marquette University
  摘要：Functional magnetic resonance imaging (fMRI) data generally consist of time series image volumes of the magnitude of complex-valued observations at each voxel. However, incorporating Gaussian-based time series models and the Rice distribution-a more accurate model for the data-in the time series have been separated by a distributional mismatch. We bridge this gap by including pth-order autoregressive (AR) errors into the Gaussian model for the latent real and imaginary components underlying th...
• IS THE PRICE CAP FOR GAS USEFUL? EVIDENCE FROM EUROPEAN COUNTRIES AI翻译
  作者：Ravazzolo, Francesco; Rossini, Luca
  作者单位：BI Norwegian Business School; Free University of Bozen-Bolzano; University of Milan; Fondazione Mattei
  摘要：Since Russia's invasion of Ukraine, many countries have pledged to end or restrict their oil and gas imports to curtail Moscow's revenues and hinder its war effort. Thus, the European ministers agreed to trigger a cap on the gas price. To detect the importance of the price cap for gas, we provide a mixture representation for the gas price to detect the presence of outliers made by a truncated normal distribution and a uniform one. We focus our analysis on a unique dataset of different commodit...
• A DEEP NEURAL NETWORK TWO-PART MODEL AND FEATURE IMPORTANCE TEST FOR SEMICONTINUOUS DATA AI翻译
  作者：Zou, Baiming; Mi, Xinlei; Wan, Shiyu; Wu, Di; Xenakis, James G.; Hu, Jianhua; Zou, Fei
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Gilead Sciences; Harvard University; Columbia University
  摘要：Semicontinuous data frequently arise in clinical practice. For example, while many surgical patients still suffer from varying degrees of acute postoperative pain (POP) sometime after surgery (i.e., POP score > 0), others experience none (i.e., POP score = 0), indicating the existence of two distinct data processes at play. Existing parametric or semiparametric two-part modeling methods for this type of semicontinuous data can fail to appropriately model the two underlying data processes, as s...
• RISK SET MATCHED DIFFERENCE-IN-DIFFERENCES FOR THE ANALYSIS OF EFFECT MODIFICATION IN AN OBSERVATIONAL STUDY ON THE IMPACT OF GUN VIOLENCE ON HEALTH OUTCOMES AI翻译
  作者：Cohn, Eric R.; Song, Zirui; Zubizarreta, Jose R.
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard Medical School; Harvard University; Harvard Medical School; Harvard University; Harvard University
  摘要：Gun violence is a major source of injury and death in the United States. However, relatively little is known about the effects of firearm injuries on survivors and their family members and how these effects vary. To study these questions and, more generally, to address a gap in the methodological causal inference literature, we present a framework for the study of effect modification or heterogeneous treatment effects in difference-in-differences designs. We implement a new matching technique,...
• LOW-RANK LONGITUDINAL FACTOR REGRESSION WITH APPLICATION TO CHEMICAL MIXTURES AI翻译
  作者：Palmer, Glenn; Herring, Amy H.; Dunson, David B.
  作者单位：Duke University
  摘要：Developmental epidemiology commonly focuses on assessing the association between multiple early life exposures and childhood health. Statistical analyses of data from such studies focus on inferring the contributions of individual exposures, while also characterizing time-varying and interacting effects. Such inferences are made more challenging by correlations among exposures, nonlinearity, and the curse of dimensionality. Motivated by studying the effects of prenatal bisphenol A (BPA) and ph...
• LEVERAGING AN OBSERVED-DATA LIKELIHOOD IMPROVES THE USE OF MACHINE LEARNING LABELS IN A BAYESIAN HIERARCHICAL MODEL FOR BIOACOUSTIC DATA AI翻译
  作者：Oram, Jacob K.; Banner, Katharine M.; Stratton, Christian; Hoegh, Andrew; Irvine, Kathryn M.
  作者单位：Montana State University System; Montana State University Bozeman; Middlebury College; United States Department of the Interior; United States Geological Survey
  摘要：Classification of massive datasets by machine learning (ML) algorithms is promising for many scientific domains, especially wildlife monitoring programs that rely on passive acoustic surveys for detecting species. However, treating ML-predicted class labels (e.g., species identity) as truth biases inferences of focal parameters within common modeling frameworks. One solution is to model the misclassification process explicitly using human-validated true-class labels for a subset of observation...
• CLUSTER ANALYSIS OF LONGITUDINAL PROFILES FOR COMPOSITIONAL COUNT DATA AI翻译
  作者：Duan, Chenyang; Jiang, Yuan
  作者单位：AbbVie; Oregon State University
  摘要：To classify biological roles of different species in an ecological system, modern studies collect longitudinal and compositional counts of DNA sequences of taxonomically diagnostic genetic markers to measure the abundance of species over time. The major challenges of conducting this analysis are twofold: how to accommodate the complex dependence in this data type and how to model the longitudinal trajectories of the species' abundances. In this paper we propose a novel method named COMPARING t...
• A PRIVACY-PRESERVED AND HIGH-UTILITY SYNTHESIS STRATEGY FOR RISK-BASED STRATIFIED SUBGROUPS OF THE CANADIAN SCLERODERMA PATIENT REGISTRY DATA AI翻译
  作者：Jiang, Bei; Raftery, Adrian E.; Steele, Russell J.; Wang, Naisyin
  作者单位：University of Alberta; University of Washington; University of Washington Seattle; McGill University; University of Michigan System; University of Michigan
  摘要：Responsible data sharing anchors research reproducibility and promotes the integrity of scientific research. Motivated by Canadian Scleroderma Research Group (CSRG) patient registry data, we present a risk-based method to produce privacy-preserved and high-utility synthetic datasets, which also simultaneously imputes missing data of mixed continuous and categorical types in the original dataset. This method divides all individuals into different subgroups, based on their reidentification risks...
• TRACING THE IMPACTS OF MOUNT PINATUBO ERUPTION ON REGIONAL CLIMATE USING SPATIALLY-VARYING CHANGEPOINT DETECTION AI翻译
  作者：Shi-Jun, Samantha; Shand, Lyndsay; Li, Bo
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; United States Department of Energy (DOE); Sandia National Laboratories
  摘要：Significant events, such as volcanic eruptions, can have global and longlasting impacts on climate. These global impacts, however, are not uniform across space and time. Understanding how the Mt. Pinatubo eruption affects global and regional climate is of great interest for predicting the impact on climate due to similar events as well as understanding the possible effect of the stratospheric aerosol injections proposed to combat climate change. While many studies illustrated the impact of the...
• BOOTSTRAPPING THE CROSS-VALIDATION ESTIMATE AI翻译
  作者：Cai, Bryan; Luo, Yuanhui; Guo, Xinzhou; Pellegrini, Fabio; Pang, Menglan; De Moor, Carl; Shen, Changyu; Charu, Vivek; Tian, Lu
  作者单位：Stanford University; Hong Kong University of Science & Technology; Biogen; Stanford Medicine; Stanford University; Stanford University
  摘要：Cross-validation is a widely used technique for evaluating the performance of prediction models, ranging from simple binary classification to complex precision medicine strategies. It helps correct for optimism bias in error estimates, which can be significant for models built using complex statistical learning algorithms. However, since the cross-validation estimate is a random value dependent on observed data, it is essential to accurately quantify the uncertainty associated with the estimat...