3期

最新文章

• MUTUALLY EXCITING POINT PROCESSES FOR CROWDFUNDINGPLATFORM DYNAMICS AI翻译
  作者：Djorno, Alexandra; Crawford, Andforrest W.
  作者单位：Yale University
  摘要：Crowdfunding is a powerful tool for individuals or organizations seekingfinancial support from a vast audience. Despite widespread adoption, man-agers often lack information about dynamics of their platforms. Hawkes pro-cesses have been used to represent self-exciting phenomenon in a wide vari-ety of empirical fields but have not been applied to crowdfunding platformsin a way that could help managers understand user behaviors. In this paperwe extend the Hawkes process to capture important feat...
• MUTUALLY EXCITING POINT PROCESSES FOR CROWDFUNDINGPLATFORM DYNAMICS AI翻译
  作者：Djorno, Alexandra; Crawford, Andforrest W.
  作者单位：Yale University
  摘要：Crowdfunding is a powerful tool for individuals or organizations seekingfinancial support from a vast audience. Despite widespread adoption, man-agers often lack information about dynamics of their platforms. Hawkes pro-cesses have been used to represent self-exciting phenomenon in a wide vari-ety of empirical fields but have not been applied to crowdfunding platformsin a way that could help managers understand user behaviors. In this paperwe extend the Hawkes process to capture important feat...
• CLUSTERING AND META-ANALYSIS USING A MIXTURE OF DEPENDENT LINEAR TAIL-FREE PRIORS AI翻译
  作者：Flores, Bernardo; Muller, Peter
  作者单位：University of Texas System; University of Texas Austin
  摘要：We propose a novel nonparametric Bayesian approach for meta-analysis with event time outcomes. The model is an extension of linear dependent tail-free processes. The extension includes a modification to facilitate (conditionally) conjugate posterior updating and a hierarchical extension with a random partition of studies. The partition is formalized as a Dirichlet process mixture. The model development is motivated by a meta-analysis of cancer immunotherapy studies. The aim is to validate the ...
• INTEGRATIVE ECOLOGICAL REGRESSION ANALYSIS OF US COUNTY AND STATE LEVEL COVID-19 DEATH DATA FOR STUDYING HEALTH DISPARITY ASSOCIATIONS AI翻译
  作者：Li, Daniel; Lin, Xihong
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health
  摘要：It is of substantial interest to study health disparity associations withCOVID-19 death rates. Although high-quality individual-level COVID-19epidemiological data have been difficult to collect on a national scale, allUnited States (U.S.) counties have reported total COVID-19 death counts.A standard ecological analysis would then regress county total death countsby county-level covariates such as age, sex, and race percentages. However,such an analysis is limited by ecological bias and fallacy...
• BAYESIAN LEARNING OF CLINICALLY MEANINGFUL SEPSIS PHENOTYPES IN NORTHERN TANZANIA AI翻译
  作者：Dombowsky, Alexander; Dunson, David B.; Madut, Deng B.; Rubach, Matthew P.; Herring, Amy H.
  作者单位：Duke University; Duke University; Duke University; Duke University; Duke University; Duke University
  摘要：Sepsis is a life-threatening condition caused by a dysregulated host response to infection. Recently, researchers have hypothesized that sepsis consists of a heterogeneous spectrum of distinct subtypes, motivating several studies to identify clusters of sepsis patients that correspond to subtypes, with the long-term goal of using these clusters to design subtype-specific treatments. Therefore, clinicians rely on clusters having a concrete medical interpretation, usually corresponding to clinic...
• BAYESIAN QUANTILE REGRESSION WITH SUBSET SELECTION:A DECISION ANALYSIS PERSPECTIVE AI翻译
  作者：Feldman, Joseph; Kowal, Daniel R.
  作者单位：Duke University; Cornell University; Rice University
  摘要：Quantile regression is a powerful tool in epidemiological studies whereinterest lies in inferring how different exposures affect specific percentilesof the distribution of a health or life outcome. Existing methods either es-timate conditional quantiles separately for each quantile of interest or esti-mate the entire conditional distribution using semi- or nonparametric models.The former often produce inadequate models for real data and do not shareinformation across quantiles, while the latte...
• GLOBAL-LOCAL DIRICHLET PROCESSES FOR IDENTIFYING PAN-CANCER SUBPOPULATIONS USING BOTH SHARED AND CANCER-SPECIFIC DATA AI翻译
  作者：Chakrabarti, Arhit; Ni, Yang; Pati, Debdeep; Mallick, Bani K.
  作者单位：Texas A&M University System; Texas A&M University College Station; University of Wisconsin System; University of Wisconsin Madison
  摘要：We consider the problem of clustering grouped data for which the observations may include group-specific variables in addition to the variables that are shared across groups. This type of data is common in cancer genomics where the molecular information is usually accompanied by cancer-specific clinical information. Existing grouped clustering methods only consider the shared variables, thereby ignoring valuable information from the cancer-specific variables. To allow for these cancer-specific...
• BAYESIAN DIFFERENTIAL CAUSAL DIRECTED ACYCLIC GRAPHS FOR OBSERVATIONAL ZERO-INFLATED COUNTS WITH AN APPLICATION TO TWO-SAMPLE SINGLE-CELL DATA AI翻译
  作者：Choi, Junsouk; Chapkin, Robert S.; Ni, Yang
  作者单位：Korea University; Texas A&M University System; Texas A&M University College Station; University of Texas System; University of Texas Austin
  摘要：Observational zero-inflated count data arise in a wide range of areas such as genomics. One of the common research questions is to identify causal relationships by learning the structure of a sparse directed acyclic graph (DAG). While structure learning of DAGs has been an active research area, existing methods do not adequately account for excessive zeros and, therefore, are not suitable for modeling zero-inflated count data. Moreover, it is often interesting to study differences in the causa...
• PSEUDO-LIKELIHOOD RATIO SCREENING BASED ON NETWORK DATA WITH APPLICATIONS AI翻译
  作者：Hu, Wei; Huang, Danyang; Zhang, Bo
  作者单位：Chinese Academy of Sciences; Renmin University of China
  摘要：Social network platforms today generate vast amounts of data, including network structures and a large number of user-defined tags, which reflect users' interests. The dimensionality of these personalized tags can be ultrahigh, posing challenges for model analysis in targeted preference analysis. Traditional categorical feature screening methods overlook the network structure, which can lead to incorrect feature set and suboptimal prediction accuracy. This study focuses on feature screening fo...
• AN ACCUMULATION METHOD FOR EARLY FAULT WARNING AND ITS APPLICATION TO WIND TURBINE SYSTEMS AI翻译
  作者：Latiffianti, Effi; Sheng, Shawn; Rodgers, Marianne; Sanderson, Robbie; Ding, Yu
  作者单位：Institut Teknologi Sepuluh Nopember; United States Department of Energy (DOE); National Renewable Energy Laboratory - USA; University System of Georgia; Georgia Institute of Technology
  摘要：Unexpected failures in engineering systems lead to expensive maintenance actions and should be avoided if at all possible. This is particularly true for wind turbine systems for which unexpected failures not only demand costly repairs but also cause long downtime. Motivated by this need, we present an accumulation method for fault early warning and failure anticipation. Our research shows that one critical element allowing the ability of early warning is to accumulate the small-magnitude sympt...