3期

最新文章

• SPARSE MEDIAN GRAPHS ESTIMATION IN A HIGH-DIMENSIONAL SEMIPARAMETRIC MODEL AI翻译
  作者：Han, Fang; Han, Xiaoyan; Liu, Han; Caffo, Brian
  作者单位：Johns Hopkins University; Johns Hopkins University; Princeton University; University of Washington; University of Washington Seattle
  摘要：We propose a unified framework for conducting inference on complex aggregated data in high-dimensional settings. We assume the data are a collection of multiple non-Gaussian realizations with underlying undirected graphical structures. Using the concept of median graphs in summarizing the commonality across these graphical structures, we provide a novel semipara-metric approach to modeling such complex aggregated data, along with robust estimation of the median graph, which is assumed to be sp...
• GENE-PROXIMITY MODELS FOR GENOME-WIDE ASSOCIATION STUDIES AI翻译
  作者：Johnston, Ian; Hancock, Timothy; Mamitsuka, Hiroshi; Carvalho, Luis
  作者单位：Boston University; Department of Primary Industries & Regional Development NSW; Kyoto University
  摘要：Motivated by the important problem of detecting association between genetic markers and binary traits in genome-wide association studies, we present a novel Bayesian model that establishes a hierarchy between markers and genes by defining weights according to gene lengths and distances from genes to markers. The proposed hierarchical model uses these weights to define unique prior probabilities of association for markers based on their proximities to genes that are believed to be relevant to t...
• DATA MINING TO INVESTIGATE THE METEOROLOGICAL DRIVERS FOR EXTREME GROUND LEVEL OZONE EVENTS AI翻译
  作者：Russell, Brook T.; Cooley, Daniel S.; Porter, William C.; Reich, Brian J.; Heald, Colette L.
  作者单位：Clemson University; Colorado State University System; Colorado State University Fort Collins; Massachusetts Institute of Technology (MIT); North Carolina State University; Massachusetts Institute of Technology (MIT)
  摘要：This project aims to explore which combinations of meteorological conditions are associated with extreme ground level ozone conditions. Our approach focuses only on the tail by optimizing the tail dependence between the ozone response and functions of meteorological covariates. Since there is a long list of possible meteorological covariates, the space of possible models cannot be explored completely. Consequently, we perform data mining within the model selection context, employing an automat...
• A HIERARCHICAL FRAMEWORK FOR STATE-SPACE MATRIX INFERENCE AND CLUSTERING AI翻译
  作者：Zuo, Chandler; Chen, Kailei; Hewitt, Kyle J.; Bresnick, Emery H.; Keles, Sunduz
  作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
  摘要：Integrative analysis of multiple experimental datasets measured over a large number of observational units is the focus of large numbers of contemporary genomic and epigenomic studies. The key objectives of such studies include not only inferring a hidden state of activity for each unit over individual experiments, but also detecting highly associated clusters of units based on their inferred states. Although there are a number of methods tailored for specific datasets, there is currently no s...