535期

最新文章

• Bayesian Semiparametric Longitudinal Drift-Diffusion Mixed Models for Tone Learning in Adults AI翻译
  作者：Paulon, Giorgio; Llanos, Fernando; Chandrasekaran, Bharath; Sarkar, Abhra
  作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：Understanding how adult humans learn nonnative speech categories such as tone information has shed novel insights into the mechanisms underlying experience-dependent brain plasticity. Scientists have traditionally examined these questions using longitudinal learning experiments under a multi-category decision making paradigm. Drift-diffusion processes are popular in such contexts for their ability to mimic underlying neural mechanisms. Motivated by these problems, we develop a novel Bayesian s...
• Training Neural Networks as Learning Data-Adaptive Kernels: Provable Representation and Approximation Benefits AI翻译
  作者：Dou, Xialiang; Liang, Tengyuan
  作者单位：University of Chicago; University of Chicago
  摘要：Consider the problem: given the data pair drawn from a population with , specify a neural network model and run gradient flow on the weights over time until reaching any stationarity. How does f(t), the function computed by the neural network at time t, relate to , in terms of approximation and representation? What are the provable benefits of the adaptive representation by neural networks compared to the prespecified fixed basis representation in the classical nonparametric literature? We ans...
• Comment on A Gibbs Sampler for a Class of Random Convex Polytopes by PE Jacob, R. Gong, PT Edlefsen and AP Dempster AI翻译
  作者：Ruggeri, Fabrizio
  作者单位：Consiglio Nazionale delle Ricerche (CNR); Istituto di Matematica Applicata e Tecnologie Informatiche Enrico Magenes (IMATI-CNR)
• Constrained Functional Regression of National Forest Inventory Data Over Time Using Remote Sensing Observations AI翻译
  作者：Khan, Md Kamrul Hasan; Chakraborty, Avishek; Petris, Giovanni; Wilson, Barry T.
  作者单位：University of Arkansas System; University of Arkansas Fayetteville; United States Department of Agriculture (USDA); United States Forest Service
  摘要：The USDA Forest Service uses satellite imagery, along with a sample of national forest inventory field plots, to monitor and predict changes in forest conditions over time throughout the United States. We specifically focus on a 230,400 ha region in north-central Wisconsin between 2003 and 2012. The auxiliary data from the satellite imagery of this region are relatively dense in space and time, and can be used to learn how forest conditions changed over that decade. However, these records have...
• Network Dependence Can Lead to Spurious Associations and Invalid Inference AI翻译
  作者：Lee, Youjin; Ogburn, Elizabeth L.
  作者单位：University of Pennsylvania; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health
  摘要：Researchers across the health and social sciences generally assume that observations are independent, even while relying on convenience samples that draw subjects from one or a small number of communities, schools, hospitals, etc. A paradigmatic example of this is the Framingham Heart Study (FHS). Many of the limitations of such samples are well-known, but the issue of statistical dependence due to social network ties has not previously been addressed. We show that, along with anticonservative...
• Comment on A Gibbs Sampler for a Class of Random Convex Polytopes, by Pierre E. Jacob, Ruobin Gong, Paul T. Edlefsen, and Arthur P. Dempster AI翻译
  作者：Shafer, Glenn
  作者单位：Rutgers University System; Rutgers University Newark; Rutgers University New Brunswick
• Discussion of A Gibbs Sampler for a Class of Random Convex Polytopes AI翻译
  作者：Diaconis, Persi; Wang, Guanyang
  作者单位：Stanford University; Rutgers University System; Rutgers University New Brunswick
• Evaluation of the Health Impacts of the 1990 Clean Air Act Amendments Using Causal Inference and Machine Learning AI翻译
  作者：Nethery, Rachel C.; Mealli, Fabrizia; Sacks, Jason D.; Dominici, Francesca
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; University of Florence; United States Environmental Protection Agency
  摘要：We develop a causal inference approach to estimate the number of adverse health events that were prevented due to changes in exposure to multiple pollutants attributable to a large-scale air quality intervention/regulation, with a focus on the 1990 Clean Air Act Amendments (CAAA). We introduce a causal estimand called the total events avoided (TEA) by the regulation, defined as the difference in the number of health events expected under the no-regulation pollution exposures and the number obs...
• Trends in Extreme Value Indices AI翻译
  作者：de Haan, Laurens; Zhou, Chen
  作者单位：Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; European Central Bank; De Nederlandsche Bank NV; Tinbergen Institute
  摘要：We consider extreme value analysis for independent but nonidentically distributed observations. In particular, the observations do not share the same extreme value index. Assuming continuously changing extreme value indices, we provide a nonparametric estimate for the functional extreme value index. Besides estimating the extreme value index locally, we also provide a global estimator for the trend and its joint asymptotic theory. The asymptotic theory for the global estimator can be used for ...
• Extreme and Inference for Tail Gini Functionals With Applications in Tail Risk Measurement AI翻译
  作者：Hou, Yanxi; Wang, Xing
  作者单位：Fudan University; Illinois Institute of Technology
  摘要：Tail risk analysis focuses on the problem of risk measurement on the tail regions of financial variables. As one crucial task in tail risk analysis for risk management, the measurement of tail risk variability is less addressed in the literature. Neither the theoretical results nor inference methods are fully developed, which results in the difficulty of modeling implementation. Practitioners are then short of measurement methods to understand and evaluate tail risks, even when they have large...