2期

最新文章

• 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 School Public Health; 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...
• 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...
• 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...
• 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 ...
• A MULTIRUN STEP-STRESS MODEL FOR TREND RENEWAL DATA WITH APPLICATIONS TO LIFETIME ASSESSMENT FOR RECHARGEABLE BATTERIES AI翻译
  作者：Tseng, Sheng-Tsaing; Hsu, Nan-Jung; Wu, Chien-Chi
  作者单位：National Tsing Hua University
  摘要：Conducting a cost-efficient lifetime-testing plan to timely assess lifetime information of a highly reliable product is often a challenging task in the manufacturing industry. Motivated by a case study of rechargeable lithium-ion batteries, this paper introduces a multirun k-level step-stress experiment, running under different stresses in repeated cycles, to collect and analyze the degradation data of reusable highly-reliable products. Specifically, we formulate the battery capacity over rech...