4期

最新文章

• THE INFORMATION IN COVARIATE IMBALANCE IN STUDIES OF HORMONE REPLACEMENT THERAPY AI翻译
  作者：Yu, Ruoqi; Small, Dylan S.; Rosenbaum, Paul R.
  作者单位：University of Pennsylvania
  摘要：A widely noted failure of causal inference occurred when several observational studies claimed that hormone replacement therapy (HRT) reduced risk of cardiovascular disease; yet, subsequent randomized trials found an increased, not a decreased, cardiovascular risk. We take a close look at covariate imbalances in one of the observational data sets. We use some old, some recent, and some new methods, plus we update an important, simple but largely forgotten suggestion of William Cochran about sc...
• ASSESSING THE RELIABILITY OF WIND POWER OPERATIONS UNDER A CHANGING CLIMATE WITH A NON-GAUSSIAN BIAS CORRECTION AI翻译
  作者：Zhang, Jiachen; Crippa, Paola; Genton, Marc G.; Castruccio, Stefano
  作者单位：University of Notre Dame; University of Notre Dame; King Abdullah University of Science & Technology
  摘要：Facing increasing societal and economic pressure, many countries have established strategies to develop renewable energy portfolios whose penetration in the market can alleviate the dependence on fossil fuels. In the case of wind, there is a fundamental question related to the resilience and hence profitability of future wind farms to a changing climate, given that current wind turbines have lifespans of up to 30 years. In this work we develop a new non-Gaussian method to adjust assimilated ob...
• SPATIAL VOTING MODELS IN CIRCULAR SPACES: A CASE STUDY OF THE US HOUSE OF REPRESENTATIVES AI翻译
  作者：Yu, Xingchen; Rodriguez, Abel
  作者单位：University of California System; University of California Santa Cruz; University of Washington; University of Washington Seattle
  摘要：The use of spatial models for inferring members' preferences from voting data has become widespread in the study of deliberative bodies, such as legislatures. Most established spatial voting models assume that ideal points belong to a Euclidean policy space. However, the geometry of Euclidean spaces (even multidimensional ones) cannot fully accommodate situations in which members at the opposite ends of the ideological spectrum reveal similar preferences by voting together against the rest of ...
• MARKOV RANDOM FIELD MODELS FOR VECTOR-BASED REPRESENTATIONS OF LANDSCAPES AI翻译
  作者：Zamberletti, Patrizia; Papaix, Julien; Gabriel, Edith; Opitz, Thomas
  作者单位：INRAE
  摘要：In agricultural landscapes the spatial distribution of cultivated and semi-natural elements strongly impacts habitat connectivity and species dynamics. To allow for landscape structural analysis and scenario generation, we here develop statistical tools for real landscapes composed of geometric elements, including 2D patches but also 1D linear elements (e.g., hedges). Utilizing the framework of discrete Markov random fields, we design generative stochastic models that combine a multiplex netwo...
• UNCERTAINTY QUANTIFICATION OF A COMPUTER MODEL FOR BINARY BLACK HOLE FORMATION AI翻译
  作者：Lin, Luyao; Bingham, Derek; Broekgaarden, Floor; Mandel, Ilya
  作者单位：Simon Fraser University; Smithsonian Astrophysical Observatory; Smithsonian Institution; Harvard University; Monash University
  摘要：In this paper, a fast and parallelizable method based on Gaussian processes (GPs) is introduced to emulate computer models that simulate the formation of binary black holes (BBHs) through the evolution of pairs of massive stars. Two obstacles that arise in this application are the a priori unknown conditions of BBH formation and the large scale of the simulation data. We address them by proposing a local emulator which combines a GP classifier and a GP regression model. The resulting emulator ...
• SPACE-TIME SMOOTHING MODELS FOR SUBNATIONAL MEASLES ROUTINE IMMUNIZATION COVERAGE ESTIMATION WITH COMPLEX SURVEY DATA AI翻译
  作者：Dong, Tracy Qi; Wakefield, Jon
  作者单位：University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle
  摘要：Despite substantial advances in global measles vaccination, measles disease burden remains high in many low- and middle-income countries. A key public health strategy for controlling measles in such high-burden settings is to conduct supplementary immunization activities (SIAs) in the form of mass vaccination campaigns, in addition to delivering scheduled vaccination through routine immunization (RI) programs. To achieve balanced implementations of RI and SIAs, robust measurement of subnationa...
• BAYESIAN MULTISTUDY FACTOR ANALYSIS FOR HIGH-THROUGHPUT BIOLOGICAL DATA AI翻译
  作者：De Vito, Roberta; Bellio, Ruggero; Trippa, Lorenzo; Parmigiani, Giovanni
  作者单位：Brown University; University of Udine; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard T.H. Chan School of Public Health
  摘要：This paper analyzes breast cancer gene expression across seven studies to identify genuine and thus replicable gene patterns shared among these studies. Our premise is that genuine biological signal is more likely to be reproducibly present in multiple studies than spurious signal. Our analysis uses a new modeling strategy for the joint analysis of high-throughput biological studies which simultaneously identifies shared as well as study-specific signal. To this end, we generalize the multi-st...
• NONPARAMETRIC IMPORTANCE SAMPLING FOR WIND TURBINE RELIABILITY ANALYSIS WITH STOCHASTIC COMPUTER MODELS AI翻译
  作者：Li, Shuoran; Ko, Young Myoung; Byon, Eunshin
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Pohang University of Science & Technology (POSTECH); University of Michigan System; University of Michigan
  摘要：Using aeroelastic stochastic simulations, this study presents an importance sampling method for assessing wind turbine reliability. As the size of modern wind turbines gets larger, structural reliability analysis becomes more important to prevent any catastrophic failures. At the design stage, operational data do not exist or are scarce. Therefore, aeroelastic simulation is often employed for reliability analysis. Importance sampling is one of the powerful variance reduction techniques to miti...
• INTEGRATING GEOSTATISTICAL MAPS AND INFECTIOUS DISEASE TRANSMISSION MODELS USING ADAPTIVE MULTIPLE IMPORTANCE SAMPLING AI翻译
  作者：Retkute, Renata; Touloupou, Panayiota; Basanez, Maria-Gloria; Hollingsworth, T. Deirdre; Spencer, Simon E. F.
  作者单位：University of Cambridge; University of Birmingham; Imperial College London; Imperial College London; University of Oxford; University of Warwick; University of Warwick
  摘要：The Adaptive Multiple Importance Sampling algorithm (AMIS) is an iterative technique which recycles samples from all previous iterations in order to improve the efficiency of the proposal distribution. We have formulated a new statistical framework, based on AMIS, to take the output from a geostatistical model of infectious disease prevalence, incidence or relative risk, and project it forward in time under a mathematical model for transmission dynamics. We adapted the AMIS algorithm so that i...
• MEDIATION ANALYSIS FOR ASSOCIATIONS OF CATEGORICAL VARIABLES: THE ROLE OF EDUCATION IN SOCIAL CLASS MOBILITY IN BRITAIN AI翻译
  作者：Kuha, Jouni; Bukodi, Erzsebet; Goldthorpe, John H.
  作者单位：University of London; London School Economics & Political Science; University of Oxford; University of Oxford
  摘要：We analyse levels and trends of intergenerational social class mobility among three postwar birth cohorts in Britain and examine how much of the observed mobility or immobility in them could be accounted for by existing differences in educational attainment between people from different class backgrounds. We propose for this purpose a method which quantifies associations between categorical variables when we compare groups which differ only in the distribution of a mediating variable, such as ...