507期

最新文章

• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models AI翻译
  作者：Fan, Jianqing; Ma, Yunbei; Dai, Wei
  作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Princeton University; Southwestern University of Finance & Economics - China
  摘要：The varying coefficient model is an important class of nonparametric statistical model, which allows us to examine how the effects of covariates vary with exposure variables. When the number of covariates is large, the issue of variable selection arises. In this article, we propose and investigate marginal nonparametric screening methods to screen variables in sparse ultra-high-dimensional varying coefficient models. The proposed nonparametric independence screening (NIS) selects variables by ...
• Identifying Genetic Variants for Addiction via Propensity Score Adjusted Generalized Kendall's Tau AI翻译
  作者：Jiang, Yuan; Li, Ni; Zhang, Heping
  作者单位：Oregon State University; Hainan Normal University; Yale University; Yale University; Sun Yat Sen University
  摘要：Identifying replicable genetic variants for addiction has been extremely challenging. Besides the common difficulties with genome-wide association studies (GWAS), environmental factors are known to be critical to addiction, and comorbidity is widely observed. Despite the importance of environmental factors and comorbidity for addiction study, few GWAS analyses adequately considered them due to the limitations of the existing statistical methods. Although parametric methods have been developed ...
• Multivariate Analysis of Longitudinal Ordinal Data With Mixed Effects Models, With Application to Clinical Outcomes in Osteoarthritis AI翻译
  作者：Laffont, Celine Marielle; Vandemeulebroecke, Marc; Concordet, Didier
  作者单位：INRAE; Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Universite de Toulouse; Ecole Nationale Veterinaire de Toulouse; Universite Toulouse III - Paul Sabatier; Universite Federale Toulouse Midi-Pyrenees (ComUE); Institut National Polytechnique de Toulouse; Novartis
  摘要：Our objective was to evaluate the efficacy of robenacoxib in osteoarthritic dogs using four ordinal responses measured repeatedly over time. We propose a multivariate probit mixed effects model to describe the joint evolution of endpoints and to evidence the intrinsic correlations between responses that are not due to treatment effect. Maximum likelihood computation is intractable within reasonable time frames. We therefore use a pairwise modeling approach in combination with a stochastic EM a...
• Filtering With Heavy Tails AI翻译
  作者：Harvey, Andrew; Luati, Alessandra
  作者单位：University of Cambridge; University of Bologna
  摘要：An unobserved components model in which the signal is buried in noise that is non-Gaussian may throw up observations that, when judged by the Gaussian yardstick, are outliers. We describe an observation-driven model, based on a conditional Student's t-distribution, which is tractable and retains some of the desirable features of the linear Gaussian model. Letting the dynamics be driven by the score of the conditional distribution leads to a specification that is not only easy to implement, but...
• Inference From Intrinsic Bayes' Procedures Under Model Selection and Uncertainty AI翻译
  作者：Womack, Andrew J.; Leon-Novelo, Luis; Casella, George
  作者单位：Indiana University System; Indiana University Bloomington; State University System of Florida; University of Florida; University of Louisiana Lafayette
  摘要：In this article, we present a fully coherent and consistent objective Bayesian analysis of the linear regression model using intrinsic priors. The intrinsic prior is a scaled mixture of g-priors and promotes shrinkage toward the subspace defined by a base (or null) model. While it has been established that the intrinsic prior provides consistent model selectors across a range of models, the posterior distribution of the model parameters has not previously been investigated. We prove that the p...
• A Bayesian Nonparametric Modeling Framework for Developmental Toxicity Studies Comment AI翻译
  作者：Mueller, Peter; Quintana, Fernando
  作者单位：University of Texas System; University of Texas Austin; Pontificia Universidad Catolica de Chile
• Functional Principal Component Analysis of Spatiotemporal Point Processes With Applications in Disease Surveillance AI翻译
  作者：Li, Yehua; Guan, Yongtao
  作者单位：Iowa State University; Iowa State University; University of Miami
  摘要：In disease surveillance applications, the disease events are modeled by spatiotemporal point processes. We propose a new class of semiparametric generalized linear mixed model for such data, where the event rate is related to some known risk factors and some unknown latent random effects. We model the latent spatiotemporal process as spatially correlated functional data, and propose Poisson maximum likelihood and composite likelihood methods based on spline approximations to estimate the mean ...
• Spatially Varying Coefficient Model for Neuroimaging Data With Jump Discontinuities AI翻译
  作者：Zhu, Hongtu; Fan, Jianqing; Kong, Linglong
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; Princeton University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; University of Alberta
  摘要：Motivated by recent work on studying massive imaging data in various neuroimaging studies, we propose a novel spatially varying coefficient model (SVCM) to capture the varying association between imaging measures in a three-dimensional volume (or two-dimensional surface) with a set of covariates. Two stylized features of neuorimaging data are the presence of multiple piecewise smooth regions with unknown edges and jumps and substantial spatial correlations. To specifically account for these tw...
• Space-Filling Fractional Factorial Designs AI翻译
  作者：Zhou, Yong-Dao; Xu, Hongquan
  作者单位：Sichuan University; University of California System; University of California Los Angeles
  摘要：Fractional factorial designs are widely used in various scientific investigations and industrial applications. Level permutation of factors could alter their geometrical structures and statistical properties. This article studies space-filling properties of fractional factorial designs under two commonly used space-filling measures, discrepancy and maximin distance. When all possible level permutations are considered, the average discrepancy is expressed as a linear combination of generalized ...
• Adaptive Confidence Bands for Nonparametric Regression Functions AI翻译
  作者：Cai, T. Tony; Low, Mark; Ma, Zongming
  作者单位：University of Pennsylvania
  摘要：This article proposes a new formulation for the construction of adaptive confidence bands (CBs) in nonparametric function estimation problems. CBs, which have size that adapts to the smoothness of the function while guaranteeing that both the relative excess mass of the function lying outside the band and the measure of the set of points where the function lies outside the band are small. It is shown that the bands adapt over a maximum range of Lipschitz classes. The adaptive CB can be easily ...