2期

最新文章

• KULLBACK-LEIBLER-BASED DISCRETE FAILURE TIME MODELS FOR INTEGRATION OF PUBLISHED PREDICTION MODELS WITH NEW TIME-TO-EVENT DATASET AI翻译
  作者：Wang, Di; Ye, Wen; Sung, Randall; Jiang, Hui; Taylor, Jeremy m. g.; Ly, Lisa; He, Kevin
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
  摘要：Prediction of time-to-event data often suffers from rare event rates, small sample sizes, high dimensionality, and low signal-to-noise ratios. Incorporating published prediction models from external large-scale studies is expected to improve the performance of prognosis prediction from internal individual-level data. However, existing integration approaches typically assume that the underlying distributions of the external and internal data sources are similar, which is often invalid. To accou...
• SENSITIVITY ANALYSIS AND POWER IN THE PRESENCE OF MANY WEAK INSTRUMENTS: APPLICATION TO THE EFFECT OF INCARCERATION ON FUTURE EARNINGS AI翻译
  作者：Ertefaie, Ashkan; Hsu, Jesse Y.; Harding, Harding; Morenoff, Jeffrey; Small, Dylan S.
  作者单位：University of Pennsylvania; University of California System; University of California Berkeley; University of Michigan System; University of Michigan; University of Pennsylvania
  摘要：This article discusses a sensitivity analysis for an instrumental variable (IV) estimate in the presence of many instruments that are weakly associated with the endogenous variable. We study the effect of imprisonment on earnings using data on individuals sentenced for felony in Michigan in the years 2003-2006. Motivated by the random assignment of judges to cases, we construct a vector of instruments based on judges' ID. Our data has two important features that cannot be handled using standar...
• FLEXIBLE BAYESIAN SPATIAL MODELING FOR UNKNOWN MISSING DATA MECHANISM IN SURVEY ANALYSIS: AN APPLICATION TO THE CHINESE GENERAL SOCIETY SURVEY AI翻译
  作者：Hu, Guanyu; Chen, Ming-Hui; Ma, Zhihua
  作者单位：University of Texas System; University of Texas Health Science Center Houston; University of Connecticut; Shenzhen University
  摘要：Social survey data are often collected from different survey centers in different regions. In some circumstances the response variables are completely observed while the covariates have missing values. In addition, the missing data patterns will vary in different geographical locations. In this article an ordinal response regression model with a log linear model for the cutpointsis extended to fit the spatial ordinal response data with missing covariates within a Bayesian framework. A signed-s...
• A DUAL-DICTIONARY MODEL FOR MINING DOMAIN-SPECIFIC CHINESE TEXTS AI翻译
  作者：Xu, Jiaze; Pand, Changzai; Deng, Ke
  作者单位：Tsinghua University; Tsinghua University; Tsinghua University
  摘要：Processing domain-specific Chinese texts is one of the most challenging tasks in natural language processing (NLP) due to the unique characteristics of Chinese and specific challenges in processing domain-specific texts. Existing NLP methods, based on supervised learning or large language models, often suffer from unstable performance in processing domain-specific Chinese texts. In this study we propose a novel statistical approach called TopWORDS-MEPA (Abbreviated as TWM) that can achieve hig...
• BAYESIAN NONPARAMETRIC CLUSTERING WITH FEATURE SELECTION FOR SPATIALLY RESOLVED TRANSCRIPTOMICS DATA AI翻译
  作者：Zhu, Bencong; Hu, Guanyu; Xu, Lin; Fan, Xiaodan; Li, Qiwei
  作者单位：Chinese University of Hong Kong; University of Texas System; University of Texas Health Science Center Houston; University of Texas System; University of Texas Southwestern Medical Center; University of Texas System; University of Texas Dallas
  摘要：The advent of next-generation sequencing-based spatially resolved transcriptomics (SRT) techniques has reshaped genomic studies by enabling high-throughput gene expression profiling while preserving spatial context. Nevertheless, inherent challenges associated with these new high-dimensional spatial data (e.g., zero inflation) pose obstacles to effective clustering, a fundamental problem in SRT data analysis. Current computational approaches often rely on heuristic data preprocessing and arbit...
• BAYESIAN INFERENCE FOR PARTIAL ORDERS FROM RANDOM LINEAR EXTENSIONS: POWER RELATIONS FROM 12TH CENTURY ROYAL ACTA AI翻译
  作者：Nicholls, Geoff K.; Lee, Jeong Eun; Karn, Nicholas; Johnson, David; Huang, Rukuang; Muir-Watt, Alexis
  作者单位：University of Oxford; University of Auckland; University of Southampton; University of Oxford; University of Oxford
  摘要：In the eleventh and twelfth centuries in England, Wales and Normandy, royal acta were legal documents in which witnesses were listed in order of social status. Any bishops present were listed as a group. For our purposes each witness-list is an ordered permutation of bishop names with a known date or date-range. Changes over time in the order bishops are listed may reflect changes in their authority. Historians would like to detect and quantify these changes. There is no reason to assume that ...
• COMPARING BASEBALL PLAYERS ACROSS ERAS VIA NOVEL FULL HOUSE MODELING AI翻译
  作者：Yan, Shen; Burgos Jr, Adrian; Kinson, Christopher; Eck, Daniel J.
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：A new methodological framework suitable for era-adjusting baseball statistics is developed in this article. Within this methodological framework specific models are motivated. We call these models Full House Models. Full House Models work by balancing the achievements of Major League Baseball (MLB) players within a given season and the size of the MLB talent pool from which a player came. We demonstrate the utility of Full House Models in an application of comparing baseball players' performan...
• THE PROPERTIES OF COVARIATE-ADAPTIVE RANDOMIZATION PROCEDURES WITH POSSIBLY UNEQUAL ALLOCATION RATIO AI翻译
  作者：Liu, Xiao; Hu, Feifang; Ma, Wei
  作者单位：Renmin University of China; George Washington University
  摘要：In clinical trials, covariate-adaptive randomization (CAR) procedures are used to balance important covariates for more convincing results and enhanced statistical efficiency. Although most CAR procedures focus on trials with 1:1 allocation ratio, the demand for unequal allocation is growing. Therefore, this paper proposes a CAR framework that unifies numerous existing procedures and can balance general (discrete, continuous, or their combinations) covariates under any allocation ratio. To eva...
• CECNN: COPULA-ENHANCED CONVOLUTIONAL NEURAL NETWORKS IN JOINT PREDICTION OF REFRACTION ERROR AND AXIAL LENGTH BASED ON ULTRA-WIDEFIELD FUNDUS IMAGES AI翻译
  作者：Zhong, Chong; Li, Yang; Yang, Danjuan; Li, Meiyan; Zhou, Xingtao; Fu, Bo; Liu, Catherine c.; Welsh, A. H.
  作者单位：Hong Kong Polytechnic University; Fudan University; Fudan University; Fudan University; Australian National University
  摘要：The ultra-widefield (UWF) fundus image is an attractive 3D biomarker in AI-aided myopia screening because it provides much richer myopia-related information. Though axial length (AL) has been acknowledged to be highly related to the two key targets of myopia screening, spherical equivalence (SE) measurement and high myopia diagnosis, its prediction based on the UWF fundus image is rarely considered. To save the high expense and time costs of measuring SE and AL, we propose the Copula-enhanced ...
• AN APPLICATION OF VINE-BASED REGRESSION TO FLIGHT LANDING DATA AI翻译
  作者：Alnasser, Hassan; Czado, Claudia
  作者单位：Technical University of Munich
  摘要：Runway overruns pose a significant challenge to aviation safety and represent the most common type of landing incident. Identifying the underlying factors contributing to runway overruns is vital for the development of effective prevention strategies. Since a few overruns are observed, the distance required for a pilot to achieve control of the aircraft, measured by the distance to decelerate to 80 knots, is used as a precursor. We propose vine copulabased distributional regression models for ...