524期

最新文章

• Fast Moment Estimation for Generalized Latent Dirichlet Models AI翻译
  作者：Zhao, Shiwen; Engelhardt, Barbara E.; Mukherjee, Sayan; Dunson, David B.
  作者单位：Duke University; Princeton University; Princeton University
  摘要：We develop a generalized method of moments (GMM) approach for fast parameter estimation in a new class of Dirichlet latent variable models with mixed data types. Parameter estimation via GMM has computational and statistical advantages over alternative methods, such as expectation maximization, variational inference, and Markov chain Monte Carlo. A key computational advantage of our method, Moment Estimation for latent Dirichlet models (MELD), is that parameter estimation does not require inst...
• Bayesian Approximate Kernel Regression With Variable Selection AI翻译
  作者：Crawford, Lorin; Wood, Kris C.; Zhou, Xiang; Mukherjee, Sayan
  作者单位：Brown University; Brown University; Brown University; Duke University; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; Duke University; Duke University; Duke University; Duke University
  摘要：Nonlinear kernel regression models are often used in statistics and machine learning because they are more accurate than linear models. Variable selection for kernel regression models is a challenge partly because, unlike the linear regression setting, there is no clear concept of an effect size for regression coefficients. In this article, we propose a novel framework that provides an effect size analog for each explanatory variable in Bayesian kernel regression models when the kernel is shif...
• A Bayesian Variable Selection Approach Yields Improved Detection of Brain Activation From Complex-Valued fMRI AI翻译
  作者：Yu, Cheng-Han; Prado, Raquel; Ombao, Hernando; Rowe, Daniel
  作者单位：University of California System; University of California Santa Cruz; King Abdullah University of Science & Technology; Marquette University
  摘要：Voxel functional magnetic resonance imaging (fMRI) time courses are complex-valued signals giving rise to magnitude and phase data. Nevertheless, most studies use only the magnitude signals and thus discard half of the data that could potentially contain important information. Methods that make use of complex-valued fMRI (CV-fMRI) data have been shown to lead to superior power in detecting active voxels when compared to magnitude-only methods, particularly for small signal-to-noise ratios (SNR...
• Diagnostic Checking in Multivariate ARMA Models With Dependent Errors Using Normalized Residual Autocorrelations AI翻译
  作者：Mainassara, Yacouba Boubacar; Saussereau, Bruno
  作者单位：Universite Marie et Louis Pasteur
  摘要：In this paper, we derive the asymptotic distribution of normalized residual empirical autocovariances and autocorrelations under weak assumptions on the noise. We propose new portmanteau statistics for vector autoregressive moving average models with uncorrelated but nonindependent innovations by using a self-normalization approach. We establish the asymptotic distribution of the proposed statistics. This asymptotic distribution is quite different from the usual chi-squared approximation used ...
• Reconciling Curvature and Importance Sampling Based Procedures for Summarizing Case Influence in Bayesian Models AI翻译
  作者：Thomas, Zachary M.; MacEachern, Steven N.; Peruggia, Mario
  作者单位：Eli Lilly; University System of Ohio; Ohio State University
  摘要：Methods for summarizing case influence in Bayesian models take essentially two forms: (1) use common divergence measures for calculating distances between the full-data posterior and the case-deleted posterior, and (2) measure the impact of infinitesimal perturbations to the likelihood to study local case influence. Methods based on approach (1) lead naturally to considering the behavior of case-deletion importance sampling weights (the weights used to approximate samples from the case-deleted...
• Inference Under Covariate-Adaptive Randomization AI翻译
  作者：Bugni, Federico A.; Canay, Ivan A.; Shaikh, Azeem M.
  作者单位：Duke University; Northwestern University; University of Chicago
  摘要：This article studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization. Here, by covariate-adaptive randomization, we mean randomization schemes that first stratify according to baseline covariates and then assign treatment status so as to achieve balance within each stratum. Our main requirement is that the randomization scheme assigns treatment status within each stratum so that the fraction of units being assigned to treatment w...
• Polynomial Accelerated Solutions to a Large Gaussian Model for Imaging Biofilms: In Theory and Finite Precision AI翻译
  作者：Parker, Albert E.; Pitts, Betsey; Lorenz, Lindsey; Stewart, Philip S.
  作者单位：Montana State University System; Montana State University Bozeman; Montana State University System; Montana State University Bozeman; Montana State University System; Montana State University Bozeman
  摘要：Three-dimensional confocal scanning laser microscope images offer dramatic visualizations of living biofilms before and after interventions. Here, we use confocal microscopy to study the effect of a treatment over time that causes a biofilm to swell and contract due to osmotic pressure changes. From these data (the video is provided in the supplementary materials), our goal is to reconstruct biofilm surfaces, to estimate the effect of the treatment on the biofilm's volume, and to quantify the ...
• Dynamic Modeling of Conditional Quantile Trajectories, With Application to Longitudinal Snippet Data AI翻译
  作者：Dawson, Matthew; Mueller, Hans-Georg
  作者单位：University of California System; University of California Davis; University of California System; University of California Davis
  摘要：Longitudinal data are often plagued with sparsity of time points where measurements are available. The functional data analysis perspective has been shown to provide an effective and flexible approach to address this problem for the case where measurements are sparse but their times are randomly distributed over an interval. Here, we focus on a different scenario where available data can be characterized as snippets, which are very short stretches of longitudinal measurements. For each subject...
• Modeling Tangential Vector Fields on a Sphere AI翻译
  作者：Fan, Minjie; Paul, Debashis; Lee, Thomas C. M.; Matsuo, Tomoko
  作者单位：University of California System; University of California Davis; University of Colorado System; University of Colorado Boulder
  摘要：Physical processes that manifest as tangential vector fields on a sphere are common in geophysical and environmental sciences. These naturally occurring vector fields are often subject to physical constraints, such as being curl-free or divergence-free. We start with constructing parametric models for curl-free and divergence-free vector fields that are tangential to the unit sphere through applying the surface gradient or the surface curl operator to a scalar random potential field on the uni...
• Mixtures of g-Priors in Generalized Linear Models AI翻译
  作者：Li, Yingbo; Clyde, Merlise A.
  作者单位：Clemson University; Duke University
  摘要：Mixtures of Zellner's g-priors have been studied extensively in linear models and have been shown to have numerous desirable properties for Bayesian variable selection and model averaging. Several extensions of g-priors to generalized linear models (GLMs) have been proposed in the literature; however, the choice of prior distribution of g and resulting properties for inference have received considerably less attention. In this article, we unify mixtures of g-priors in GLMs by assigning the tru...