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最新文章

• ANALYSING DYNAMIC CROSS-PRICE DEPENDENCIES WITH A MARKOV-SWITCHING SPATIAL AUTOREGRESSIVE MODEL AI翻译
  作者：Iacopini, Matteo; Krisztin, Tamas; Piribauer, Philipp
  作者单位：Luiss Guido Carli University; International Institute for Applied Systems Analysis (IIASA)
  摘要：This study introduces a novel Markov-switching spatial autoregressive (MS-SAR) model to analyse dynamic cross-price interdependencies within the three-digit subcomponents of the Consumer Price Index (CPI) for 15 European Union countries. By allowing the spatial weight matrix and network strength to evolve over time, our model captures the complex, time-varying nature of economic interdependencies that traditional models often overlook. Our results reveal marked cross-country differences in the...
• RANDOM FORESTS AND MIXED EFFECTS RANDOM FORESTS FOR SMALL AREA ESTIMATION OF GENERAL PARAMETERS: A POVERTY MAPPING CASE STUDY IN MOZAMBIQUE AI翻译
  作者：Krennmair, Patrick; Wurz, Nora; Schmid, Timo; Tzavidis, Nikos
  作者单位：Free University of Berlin; Otto Friedrich University Bamberg; University of Southampton; University of Southampton
  摘要：Use of standard random forests may not guarantee reliable small area estimates unless a rich source of predictors explains the between-area heterogeneity. We propose mixed effects random forests with area random effects for small area estimation of general parameters. A new fitting algorithm with an embedded bootstrap-bias correction for the random forest residual variance is presented. Point estimators of small area parameters are constructed using a smearing estimator of the area-specific di...
• ASSESSING INFLUENTIAL OBSERVATIONS IN PAIN PREDICTION USING FMRI DATA AI翻译
  作者：Zhang, Dongliang; Asgharian, Masoud; Lindquist, Martin A.
  作者单位：Johns Hopkins University; McGill University
  摘要：Neuroimaging data allows researchers to model the relationship between multivariate patterns of brain activity and outcomes related to mental states and behaviors. However, the existence of outlying participants can potentially undermine the generalizability of these models and jeopardize the validity of downstream statistical analysis. To date, the ability to detect and account for participants unduly influencing various model selection approaches have been sorely lacking. Motivated by a task...
• MULTILEVEL FUNCTIONAL DISTRIBUTIONAL MODELS WITH APPLICATIONS TO CONTINUOUS GLUCOSE MONITORING IN DIABETES CLINICAL TRIALS AI翻译
  作者：Matabuena, Marcos; Crainiceanu, Ciprian M.
  作者单位：Mohamed bin Zayed University of Artificial Intelligence MBZUAI; Johns Hopkins University
  摘要：Continuous glucose monitoring (CGM) is a minimally invasive technology that measures blood glucose every few minutes for weeks or months at a time. CGM data are often collected in the free-living environment and is strongly related to sleep, physical activity, and meal intake. As the timing of these activities varies substantially within-and between-individuals, it is difficult to model CGM trajectories as a function of time of day. Therefore, in practice, CGM trajectories are often reduced to...
• TEMPORAL MODELS FOR ESTIMATION AND SHORT-TERM FORECASTING OF NEONATAL MORTALITY RATES IN SUB-SAHARAN AFRICA AI翻译
  作者：Paulson, Katherine R.; Fuglstad, Geir-Arne; Li, Zehang Richard; Wakefield, Jonathan
  作者单位：University of Washington; University of Washington Seattle; Norwegian University of Science & Technology (NTNU); University of California System; University of California Santa Cruz; University of Washington; University of Washington Seattle
  摘要：Accurate estimation and forecasts for neonatal mortality rates (NMRs) in low-and middle-income countries is an urgent problem. Much of child mortality is preventable, and understanding temporal trends is of great interest when evaluating past performance and planning future policy or programming. In countries without robust vital registration, we rely on modeled estimates based on survey data to understand trends. A toolkit of compelling temporal models exists, but these methods have not been ...
• DO LARGE LANGUAGE MODELS (REALLY) NEED STATISTICAL FOUNDATIONS? AI翻译
  作者：Su, Weijie
  作者单位：University of Pennsylvania
  摘要：Large language models (LLMs) represent a new paradigm for processing unstructured data, with applications across an unprecedented range of domains. In this paper we address, through two arguments, whether the development and application of LLMs would genuinely benefit from foundational contributions from the statistics discipline. First, we argue affirmatively, beginning with the observation that LLMs are inherently statistical models due to their profound data dependency and stochastic genera...
• BRIDGING THE GAP: ENHANCING THE GENERALIZABILITY OF EPIGENETIC CLOCKS THROUGH TRANSFER LEARNING AI翻译
  作者：Luo, Lan; Shang, Lulu; Goodrich, Jaclyn M.; Peterson, Karen E.; Song, Peter X. K.
  作者单位：Rutgers University System; Rutgers University New Brunswick; University of Texas System; UTMD Anderson Cancer Center; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Changes in DNA methylation patterns exhibit a high correlation with chronological age. Epigenetic clocks, developed through statistical models that estimate epigenetic age using the methylation levels of cytosine-guanine dinucleotide (CpG) sites, have emerged as powerful tools for understanding aging and age-related diseases. Despite their popularity, the generalizability of these clocks across diverse populations remains a challenge. Some of the widely used epigenetic clocks, such as Horvath'...
• NEURAL POSTERIOR ESTIMATION WITH AUTOREGRESSIVE TILING FOR DETECTING OBJECTS IN ASTRONOMICAL IMAGES AI翻译
  作者：Regier, Jeffrey
  作者单位：University of Michigan System; University of Michigan
  摘要：Upcoming astronomical surveys will produce petabytes of high-resolution images of the night sky, providing information about billions of stars and galaxies. Detecting and characterizing the astronomical objects in these images is a fundamental task in astronomy-and a challenging one, as most of these objects are faint and many visually overlap with other objects. We propose an amortized variational inference procedure to solve this instance of small-object detection. Our key innovation is a fa...
• A PARTIALLY COLLAPSED GIBBS SAMPLING ALGORITHM FOR REGRESSION WITH MISREPORTED RESPONSE AI翻译
  作者：Wang, Jiaying; Shen, Weining; Wang, Yuan
  作者单位：Washington State University; University of California System; University of California Irvine; Washington State University
  摘要：In this paper our objective is to identify the risk factors associated with adolescent marijuana use in Washington State, utilizing data from the 2018 and 2021 Healthy Youth Survey (HYS). Despite the survey's assurance of anonymity, the possibility of over-or underreporting exists due to various reasons, such as fear of being exposed, social stigma, and peer pressure. We are also interested in identifying factors that are associated with the occurrence of misreport. To achieve these goals, we ...
• MULTIPLY ROBUST ESTIMATION FOR CAUSAL SURVIVAL ANALYSIS WITH TREATMENT NONCOMPLIANCE AI翻译
  作者：Cheng, Chao; Liu, Bo; Wruck, Lisa; Li, Fan
  作者单位：Washington University (WUSTL); Duke University; Duke University; Duke University; Yale University
  摘要：Comparative effectiveness research frequently addresses a time-to-event outcome and can require unique considerations in the presence of treatment noncompliance. Motivated by the challenges in addressing noncompliance in the ADAPTABLE pragmatic clinical trial, we develop a multiply robust estimator to estimate the principal survival causal effects under the principal ignorability and monotonicity. The multiply robust estimator is consistent, even if one, and sometimes two, of the required mode...