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作者：Chen, Xi; Liu, Weidong; Zhang, Yichen
作者单位：New York University; Shanghai Jiao Tong University; Purdue University System; Purdue University
摘要：This article studies distributed estimation and inference for a general statistical problem with a convex loss that could be nondifferentiable. For the purpose of efficient computation, we restrict ourselves to stochastic first-order optimization, which enjoys low per-iteration complexity. To motivate the proposed method, we first investigate the theoretical properties of a straightforward divide-and-conquer stochastic gradient descent approach. Our theory shows that there is a restriction on ...
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作者：Wang, Lazhi; Jones, David E.; Meng, Xiao-Li
作者单位：Texas A&M University System; Texas A&M University College Station; Harvard University
摘要：Bridge sampling is an effective Monte Carlo (MC) method for estimating the ratio of normalizing constants of two probability densities, a routine computational problem in statistics, physics, chemistry, and other fields. The MC error of the bridge sampling estimator is determined by the amount of overlap between the two densities. In the case of unimodal densities, Warp-I, II, and III transformations are effective for increasing the initial overlap, but they are less so for multimodal densitie...
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作者：Zou, Changliang; Ke, Yuan; Zhang, Wenyang
作者单位：Nankai University; University System of Georgia; University of Georgia; University of York - UK
摘要：In this article, we study low rank high-dimensional multivariate linear models (LRMLM) for high-dimensional multi-response data. We propose an intuitively appealing estimation approach and develop an algorithm for implementation purposes. Asymptotic properties are established to justify the estimation procedure theoretically. Intensive simulation studies are also conducted to demonstrate performance when the sample size is finite, and a comparison is made with some popular methods from the lit...
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作者：Geenens, Gery; de Micheaux, Pierre Lafaye
作者单位：University of New South Wales Sydney
摘要：In this article, the defining properties of any valid measure of the dependence between two continuous random variables are revisited and complemented with two original ones, shown to imply other usual postulates. While other popular choices are proved to violate some of these requirements, a class of dependence measures satisfying all of them is identified. One particular measure, that we call the Hellinger correlation, appears as a natural choice within that class due to both its theoretical...
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作者：Hu, Yingtian; Zeydabadinezhad, Mahmoud; Li, Longchuan; Guo, Ying
作者单位：Emory University; Emory University
摘要：Recent advancements of multimodal neuroimaging such as functional MRI (fMRI) and diffusion MRI (dMRI) offer unprecedented opportunities to understand brain development. Most existing neurodevelopmental studies focus on using a single imaging modality to study microstructure or neural activations in localized brain regions. The developmental changes of brain network architecture in childhood and adolescence are not well understood. Our study made use of dMRI and resting-state fMRI imaging datas...
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作者：Christiansen, Rune; Baumann, Matthias; Kuemmerle, Tobias; Mahecha, Miguel D.; Peters, Jonas
作者单位：University of Copenhagen; Humboldt University of Berlin; Humboldt University of Berlin; Leipzig University; German Research Foundation (DFG); German Centre for Integrative Biodiversity Research (iDiv)
摘要：How does armed conflict influence tropical forest loss? For Colombia, both enhancing and reducing effect estimates have been reported. However, a lack of causal methodology has prevented establishing clear causal links between these two variables. In this work, we propose a class of causal models for spatio-temporal stochastic processes which allows us to formally define and quantify the causal effect of a vector of covariates X on a real-valued response Y. We introduce a procedure for estimat...
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作者：Jialin, Ouyang; Yuan, Ming
作者单位：Columbia University
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作者：Shin, Minsuk; Liu, Jun S.
作者单位：University of South Carolina System; University of South Carolina Columbia; Harvard University
摘要：Although Bayesian variable selection methods have been intensively studied, their routine use in practice has not caught up with their non-Bayesian counterparts such as Lasso, likely due to difficulties in both computations and flexibilities of prior choices. To ease these challenges, we propose the neuronized priors to unify and extend some popular shrinkage priors, such as Laplace, Cauchy, horseshoe, and spike-and-slab priors. A neuronized prior can be written as the product of a Gaussian we...
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作者：Zhao, Jiwei; Ma, Yanyuan
作者单位：University of Wisconsin System; University of Wisconsin Madison; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：We consider the estimation problem in a regression setting where the outcome variable is subject to nonignorable missingness and identifiability is ensured by the shadow variable approach. We propose a versatile estimation procedure where modeling of missingness mechanism is completely bypassed. We show that our estimator is easy to implement and we derive the asymptotic theory of the proposed estimator. We also investigate some alternative estimators under different scenarios. Comprehensive s...
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作者：Zhao, Sihai Dave; Biscarri, William
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; Capital One Financial Corporation
摘要：Problems involving the simultaneous estimation of multiple parameters arise in many areas of theoretical and applied statistics. A canonical example is the estimation of a vector of normal means. Frequently, structural information about relationships between the parameters of interest is available. For example, in a gene expression denoising problem, genes with similar functions may have similar expression levels. Despite its importance, structural information has not been well-studied in the ...
