521期

最新文章

• Multi-Armed Bandit for Species Discovery: A Bayesian Nonparametric Approach AI翻译
  作者：Battiston, Marco; Favaro, Stefano; Teh, Yee Whye
  作者单位：Bocconi University; University of Turin; Collegio Carlo Alberto; University of Oxford
  摘要：Let (P-1, ..., P-J) denote J populations of animals from distinct regions. A priori, it is unknown which species are present in each region and what are their corresponding frequencies. Species are shared among populations and each species can be present in more than one region with its frequency varying across populations. In this article, we consider the problem of sequentially sampling these populations to observe the greatest number of different species. We adopt a Bayesian nonparametric a...
• Mission CO2ntrol: A Statistical Scientist's Role in Remote Sensing of Atmospheric Carbon Dioxide Comment AI翻译
  作者：Genton, Marc G.; Jeong, Jaehong
  作者单位：King Abdullah University of Science & Technology
• Bayesian Semiparametric Multivariate Density Deconvolution AI翻译
  作者：Sarkar, Abhra; Pati, Debdeep; Chakraborty, Antik; Mallick, Bani K.; Carroll, Raymond J.
  作者单位：Duke University; University of Texas System; University of Texas Austin; State University System of Florida; Florida State University; Texas A&M University System; Texas A&M University College Station; University of Technology Sydney
  摘要：We consider the problem of multivariate density deconvolution when interest lies in estimating the distribution of a vector valued random variable X but precise measurements on X are not available, observations being contaminated by measurement errors U. The existing sparse literature on the problem assumes the density of the measurement errors to be completely known. We propose robust Bayesian semiparametric multivariate deconvolution approaches when the measurement error density of U is not ...
• Mission CO2ntrol: A Statistical Scientist's Role in Remote Sensing of Atmospheric Carbon Dioxide Comment AI翻译
  作者：Christensen, William F.; Reese, C. Shane
  作者单位：Brigham Young University; Brigham Young University
• A Potential Tale of Two-by-Two Tables From Completely Randomized Experiments (vol 111, pg 157, 2016) AI翻译
  作者：Ding, P.; Dasgupta, T.
• Embracing the Blessing of Dimensionality in Factor Models AI翻译
  作者：Li, Quefeng; Cheng, Guang; Fan, Jianqing; Wang, Yuyan
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Purdue University System; Purdue University; Princeton University; Fudan University
  摘要：Factor modeling is an essential tool for exploring intrinsic dependence structures among high-dimensional random variables. Much progress has been made for estimating the covariance matrix from a high-dimensional factor model. However, the blessing of dimensionality has not yet been fully embraced in the literature: much of the available data are often ignored in constructing covariance matrix estimates. If our goal is to accurately estimate a covariance matrix of a set of targeted variables, ...
• Variable Selection for Skewed Model-Based Clustering: Application to the Identification of Novel Sleep Phenotypes AI翻译
  作者：Wallace, Meredith L.; Buysse, Daniel J.; Germain, Anne; Hall, Martica H.; Iyengar, Satish
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：In sleep research, applying finite mixture models to sleep characteristics captured through multiple data types, including self-reported sleep diary, a wrist monitor capturing movement (actigraphy), and brain waves (polysomnography), may suggest new phenotypes that reflect underlying disease mechanisms. However, a direct mixture model application is challenging because there are many sleep variables from which to choose, and sleep variables are often highly skewed even in homogenous samples. M...