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作者：Wang, Huixia Judy; Li, Deyuan
作者单位：North Carolina State University; Fudan University
摘要：The estimation of extreme conditional quantiles is an important issue in numerous disciplines. Quantile regression (QR) provides a natural way to capture the covariate effects at different tails of the response distribution. However, without any distributional assumptions, estimation from conventional QR is often unstable at the tails, especially for heavy-tailed distributions due to data sparsity. In this article, we develop a new three-stage estimation procedure that integrates QR and extrem...
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作者：Murray, Jared S.; Dunson, David B.; Carin, Lawrence; Lucas, Joseph E.
作者单位：Duke University; Duke University; Duke University
摘要：Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models accommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables, the latent variables typically influence both the dependence structure and the form of the marginal...
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作者：Ho, Man-Wai; Tu, Wanzhu; Ghosh, Pulak; Tiwari, Ram C.
作者单位：National University of Singapore; Indiana University System; Indiana University Bloomington; Indian Institute of Management (IIM System); Indian Institute of Management Bangalore; US Food & Drug Administration (FDA)
摘要：In cluster randomized trials, patients seen by the same physician are randomized to the same treatment arm as a group. Besides the natural clustering of patients due to cluster/group randomization, interactions between an individual patient and the attending physician within the group could just as well influence patient care outcomes. Despite the intuitive relevance of these interactions to treatment assessment, few studies have thus far examined their influences. Whether and to what extent t...
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作者：Linzer, Drew A.
作者单位：Emory University
摘要：I present a dynamic Bayesian forecasting model that enables early and accurate prediction of U.S. presidential election outcomes at the state level. The method systematically combines information from historical forecasting models in real time with results from the large number of state-level opinion surveys that are released publicly during the campaign. The result is a set of forecasts that are initially as good as the historical model, and then gradually increase in accuracy as Election Day...
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作者：Davidian, Marie
作者单位：North Carolina State University
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作者：Hahn, P. Richard; Carvalho, Carlos M.; Mukherjee, Sayan
作者单位：University of Chicago; University of Texas System; University of Texas Austin; Duke University; Duke University
摘要：We develop a modified Gaussian factor model for the purpose of inducing predictor-dependent shrinkage for linear regression. The new model predicts well across a wide range of covariance structures, on real and simulated data. Furthermore, the new model facilitates variable selection in the case of correlated predictor variables, which often stymies other methods.
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作者：Martin, Ryan; Liu, Chuanhai
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Purdue University System; Purdue University
摘要：This is to provide corrections to Theorems 1 and 3 in Martin and Liu (2013). The latter correction also casts further light on the role of nested predictive random sets.
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作者：Zhang, Jingfei; Chen, Yuguo
作者单位：University of Illinois System; University of Illinois Urbana-Champaign
摘要：Random graphs with given vertex degrees have been widely used as a model for many real-world complex networks. However, both statistical inference and analytic study of such networks present great challenges. In this article, we propose a new sequential importance sampling method for sampling networks with a given degree sequence. These samples can be used to approximate closely the null distributions of a number of test statistics involved in such networks and provide an accurate estimate of ...
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作者：Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Maity, Arnab; Carroll, Raymond J.
作者单位：Simon Fraser University; Texas A&M University System; Texas A&M University College Station; North Carolina State University
摘要：Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Mo...
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作者：Chakraborty, Avishek; Mallick, Bani K.; McClarren, Ryan G.; Kuranz, Carolyn C.; Bingham, Derek; Grosskopf, Michael J.; Rutter, Erica M.; Stripling, Hayes F.; Drake, R. Paul
作者单位：Texas A&M University System; Texas A&M University College Station; Texas A&M University System; Texas A&M University College Station; University of Michigan System; University of Michigan; Simon Fraser University
摘要：Radiation hydrodynamics and radiative shocks are of fundamental interest in the high-energy-density physics research due to their importance in understanding astrophysical phenomena such as supernovae. In the laboratory, experiments can produce shocks with fundamentally similar physics on reduced scales. However, the cost and time constraints of the experiment necessitate use of a computer algorithm to generate a reasonable number of outputs for making valid inference. We focus on modeling emu...
