1期

最新文章

• DO FORECASTS OF BANKRUPTCY CAUSE BANKRUPTCY? A MACHINE LEARNING SENSITIVITY ANALYSIS AI翻译
  作者：Papakostas, Demetrios; Hahn, P. Richard; Murry, Jared; Zhou, Frank; Gerakos, Joseph
  作者单位：Arizona State University; Arizona State University-Tempe; University of Texas System; University of Texas Austin; University of Pennsylvania; Dartmouth College
  摘要：It is widely speculated that auditors' public forecasts of bankruptcy are, at least in part, self-fulfilling prophecies in the sense that they actually cause bankruptcies that would not have otherwise occurred. This conjecture is hard to prove, however, because the strong association between bankruptcies and bankruptcy forecasts could simply indicate that auditors are skillful forecasters with unique access to highly predictive covariates. In this paper we investigate the causal effect of bank...
• NESTED CONFORMAL PREDICTION SETS FOR CLASSIFICATION WITH APPLICATIONS TO PROBATION DATA AI翻译
  作者：Kuchibhotla, Arun K.; Berk, Richard A.
  作者单位：Carnegie Mellon University; University of Pennsylvania
  摘要：Risk assessments to help inform criminal justice decisions have been used in the United States since the 1920s. Over the past several years, statistical learning risk algorithms have been introduced amid much controversy about fairness, transparency and accuracy. In this paper we focus on accuracy for a large department of probation and parole that is considering a major revision of its current, statistical learning risk methods. Because the content of each offender's supervision is substantia...
• TEAM: A MULTIPLE TESTING ALGORITHM ON THE AGGREGATION TREE FOR FLOW CYTOMETRY ANALYSIS AI翻译
  作者：Pura, John A.; Li, Xuechan; Chan, Cliburn; Xie, Jichun
  作者单位：US Department of Veterans Affairs; Veterans Health Administration (VHA); Durham VA Medical Center; Duke University
  摘要：In immunology studies, flow cytometry is a commonly used multivari-ate single-cell assay. One key goal in flow cytometry analysis is to detect the immune cells responsive to certain stimuli. Statistically, this problem can be translated into comparing two protein expression probability density func-tions (PDFs) before and after the stimulus; the goal is to pinpoint the regions where these two PDFs differ. Further screening of these differential regions can be performed to identify enriched set...
• MANY-TO-ONE INDIRECT SAMPLING WITH APPLICATION TO THE FRENCH POSTAL TRAFFIC ESTIMATION AI翻译
  作者：Medous, Estelle; Goga, Camelia; Ruiz-Gazen, Anne; Beaumont, Jean-Francois; Dessertaine, Alain; Puech, Pauline
  作者单位：Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics; Universite Marie et Louis Pasteur; Statistics Canada
  摘要：In social and economic surveys, it can be difficult to directly reach units of the target population, and indirect sampling is often advocated to solve this issue. In indirect sampling, the sample is drawn from a frame population that is linked to the target population, and estimation of target population pa-rameters is typically achieved through the generalized weight share method (GWSM). This method provides a weight, for every unit of the target popu-lation, that depends on the one hand, on...
• CONEX-CONNECT: LEARNING PATTERNS IN EXTREMAL BRAIN CONNECTIVITY FROM MULTICHANNEL EEG DATA AI翻译
  作者：Guerrero, Matheus B.; Huser, Raphael; Ombao, Hernando
  作者单位：King Abdullah University of Science & Technology
  摘要：Epilepsy is a chronic neurological disorder; it affects more than 50 million people globally. An epileptic seizure acts like a temporary shock to the neuronal system, disrupting normal electrical activity in the brain. Epilepsy is frequently diagnosed with electroencephalograms (EEGs). Current methods study only the time-varying spectra and coherence but do not directly model changes in extreme behavior, neglecting the fact that neuronal oscillations exhibit non-Gaussian heavy-tailed probabili...
• STATISTICAL MATCHING AND SUBCLASSIFICATION WITH A CONTINUOUS DOSE: CHARACTERIZATION, ALGORITHM, AND APPLICATION TO A HEALTH OUTCOMES STUDY AI翻译
  作者：Zhang, B. O.; Mackay, Emily J.; Baiocchi, M. I. K. E.
  作者单位：Fred Hutchinson Cancer Center; University of Pennsylvania; Stanford University
  摘要：Subclassification and matching are often used in empirical studies to adjust for observed covariates; however, they are largely restricted to rela-tively simple study designs with a binary treatment and less developed for designs with a continuous exposure. Matching with exposure doses is partic-ularly useful in instrumental variable designs and in understanding the dose -response relationships. In this article we propose two criteria for optimal sub-classification based on subclass homogeneit...
• BAYESIAN CLUSTERING OF SPATIAL FUNCTIONAL DATA WITH APPLICATION TO A HUMAN MOBILITY STUDY DURING COVID-19 AI翻译
  作者：Zhang, By Bohai; Sang, Huiyan; Luo, Zhao Tang; Huang, Hui
  作者单位：Nankai University; Texas A&M University System; Texas A&M University College Station; Sun Yat Sen University
  摘要：The coronavirus (COVID-19) global pandemic has made a significant impact on people's social activities. Cell phone mobility data provide unique and rich information on studying this impact. The motivating dataset of this study is the daily leaving-home index data at Harris County in Texas provided by SafeGraph. To study changes in daily leaving-home index and how they relate to public policy and sociodemographic variables, we propose a new Bayesian wavelet model for modeling and clustering spa...
• REGULARIZED FINGERPRINTING IN DETECTION AND ATTRIBUTION OF CLIMATE CHANGE WITH WEIGHT MATRIX OPTIMIZING THE AI翻译
  作者：Li, Yan; Chen, Kun; Yan, Jun; Zhan, Xuebin
  作者单位：University of Connecticut; Environment & Climate Change Canada
  摘要：Detection and attribution analyses play a central role in establishing the causal effect of human activities on global warming. The most commonly used method in such analyses, optimal fingerprinting, is a multiple regression where each covariate has a measurement error whose covariance matrix is the same as that of the regression error up to a known scale. Inferences about the regression coefficients are critical not only for making statements about detection and attribution but also for quant...
• SUBJECT-SPECIFIC DIRICHLET-MULTINOMIAL REGRESSION FOR MULTI-DISTRICT MICROBIOTA DATA ANALYSIS AI翻译
  作者：Pedone, Matteo; Amedei, Amedeo; Stingo, Francesco C.
  作者单位：University of Florence; University of Florence
  摘要：Many environments within the human body host a collection of micro-organisms called microbiota. Recent findings have linked the composition of the microbiota to the development of different human diseases, includ-ing cancer. Motivated by a recent colorectal cancer (CRC) study, we inves-tigate the effect of clinical factors and diet-related covariates on the micro -biota compositions; for the patients enrolled in this study, microbiota abun-dance counts are collected from three different distri...
• A MULTIVARIATE FREQUENCY-SEVERITY FRAMEWORK FOR HEALTHCARE DATA BREACHES AI翻译
  作者：Sun, Hong; Xu, Maochao; Zhao, Peng
  作者单位：Lanzhou University; Illinois State University; Jiangsu Normal University
  摘要：Data breaches in healthcare have become a substantial concern in recent years and cause millions of dollars in financial losses each year. It is fundamental for government regulators, insurance companies, and stakeholders to understand the breach frequency and the number of affected individuals in each state, as these are directly related to the federal Health Insurance Portability and Accountability Act (HIPAA) and state data breach laws. However, an obstacle to studying data breaches in heal...