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作者：Hoshino, Takahiro
作者单位：Nagoya University
摘要：We propose a new semiparametric Bayesian model for causal inference in which assignment to treatment depends on potential outcomes. The model uses the probit stick-breaking process mixture proposed by Chung and Dunson (2009), a variant of the Dirichlet process mixture modeling. In contrast to previous Bayesian models, the proposed model directly estimates the parameters of the marginal parametric model of potential outcomes, while it relaxes the strong ignorability assumption, and requires no ...
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作者：Li, Yehua; Wang, Naisyin; Carroll, Raymond J.
作者单位：Iowa State University; University of Michigan System; University of Michigan; Texas A&M University System; Texas A&M University College Station
摘要：Functional principal component analysis (FPCA) has become the most widely used dimension reduction tool for functional data analysis. We consider functional data measured at random, subject-specific time points, contaminated with measurement error, allowing for both sparse and dense functional data, and propose novel information criteria to select the number of principal component in such data. We propose a Bayesian information criterion based on marginal modeling that can consistently select ...
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作者：Zeng, Donglin; Wang, Yuanjia
作者单位：University of North Carolina; University of North Carolina Chapel Hill; Columbia University
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作者：Yu, Tao; Li, Pengfei
作者单位：National University of Singapore; University of Waterloo
摘要：Diffusion tensor imaging (DTI), based on the diffusion-weighted imaging (DWI) data acquired from magnetic resonance experiments, has been widely used to analyze the physical structure of white-matter fibers in the human brain in vivo. The raw DWI data, however, carry noise; this contaminates the diffusion tensor (DT) estimates and introduces systematic bias into the induced eigenvalues. These bias components affect the effectiveness of fiber-tracking algorithms. In this article, we propose a t...
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作者：Ghosh, Arpita; Wright, Fred A.; Zou, Fei
作者单位：Public Health Foundation of India; University of North Carolina; University of North Carolina Chapel Hill
摘要：It has been repeatedly shown that in case control association studies, analysis of a secondary trait that ignores the original sampling scheme can produce highly biased risk estimates. Although a number of approaches have been proposed to properly analyze secondary traits, most approaches fail to reproduce the marginal logistic model assumed for the original case control trait and/or do not allow for interaction between secondary trait and genotype marker on primary disease risk. In addition, ...
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作者：Hanks, Ephraim M.; Hooten, Mevin B.
作者单位：Colorado State University System; Colorado State University Fort Collins; United States Department of the Interior; United States Geological Survey; Colorado State University System; Colorado State University Fort Collins
摘要：Circuit theory has seen extensive recent use in the field of ecology, where it is often applied to study functional connectivity. The landscape is typically represented by a network of nodes and resistors, with the resistance between nodes a function of landscape characteristics. The effective distance between two locations on a landscape is represented by the resistance distance between the nodes in the network. Circuit theory has been applied to many other scientific fields for exploratory a...
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作者：Weinstein, Asaf; Fithian, William; Benjamini, Yoav
作者单位：University of Pennsylvania; Stanford University; Tel Aviv University; Tel Aviv University
摘要：In many current large-scale problems, confidence intervals (CIs) are constructed only for the parameters that are large, as indicated by their estimators, ignoring the smaller parameters. Such selective inference poses a problem to the usual marginal CIs that no longer offer the right level of coverage, not even on the average over the selected parameters. We address this problem by developing three methods to construct short and valid CIs for the location parameter of a symmetric unimodal dis...
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作者：Raymer, James; Wisniowski, Arkadiusz; Forster, Jonathan J.; Smith, Peter W. F.; Bijak, Jakub
作者单位：University of Southampton
摘要：International migration data in Europe are collected by individual countries with separate collection systems and designs. As a result, reported data are inconsistent in availability, definition, and quality. In this article, we propose a Bayesian model to overcome the limitations of the various data sources. The focus is on estimating recent international migration flows among 31 countries in the European Union and European Free Trade Association from 2002 to 2008, using data collated by Euro...
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作者：Liang, Faming; Cheng, Yi Hen; Song, Qifan; Park, Jincheol; Yang, Ping
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
摘要：The Gaussian geostatistical model has been widely used in modeling of spatial data. However, it is challenging to computationally implement this method because it requires the inversion of a large covariance matrix, particularly when there is a large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the current estimate o...
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作者：Mammen, Enno
作者单位：University of Mannheim
