-
作者：Zhang, Ting; Lavitas, Liliya
作者单位：Boston University
摘要：We propose a new self-normalized method for testing change points in the time series setting. Self-normalization has been celebrated for its ability to avoid direct estimation of the nuisance asymptotic variance and its flexibility of being generalized to handle quantities other than the mean. However, it was developed and mainly studied for constructing confidence intervals for quantities associated with a stationary time series, and its adaptation to change-point testing can be nontrivial as...
-
作者：Bassetti, Federico; Casarin, Roberto; Ravazzolo, Francesco
作者单位：University of Pavia; Universita Ca Foscari Venezia; Free University of Bozen-Bolzano
摘要：We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights. Building on the work of Ranjan and Gneiting, we use infinite beta mixtures for the calibration. The proposed Bayesian nonparametric approach takes advantage of the flexibility of Dirichlet process mixtures to achieve any continuous deformation of linearly combined...
-
作者：Christensen, William F.; Reese, C. Shane
作者单位：Brigham Young University; Brigham Young University
-
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...
-
作者：Swanson, Sonja A.; Hernan, Miguel A.; Miller, Matthew; Robins, James M.; Richardson, Thomas S.
作者单位：Erasmus University Rotterdam; Erasmus MC; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Northeastern University; University of Washington; University of Washington Seattle
摘要：Several methods have been proposed for partially or point identifying the average treatment effect (ATE) using instrumental variable (IV) type assumptions. The descriptions of these methods are widespread across the statistical, economic, epidemiologic, and computer science literature, and the connections between the methods have not been readily apparent. In the setting of a binary instrument, treatment, and outcome, we review proposed methods for partial and point identification of the ATE u...
-
作者：Yao, Zhigang; Zhang, Ye; Bai, Zhidong; Eddy, William F.
作者单位：National University of Singapore; Orebro University; Northeast Normal University - China; Northeast Normal University - China; Carnegie Mellon University
摘要：Magnetoencephalography (MEG) is an advanced imaging technique used to measure the magnetic fields outside the human head produced by the electrical activity inside the brain. Various source localization methods in MEG require the knowledge of the underlying active sources, which are identified by a priori. Common methods used to estimate the number of sources include principal component analysis or information criterion methods, both of which make use of the eigenvalue distribution of the data...
-
作者：Ding, P.; Dasgupta, T.
-
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...
-
作者：Li, Quefeng; Cheng, Guang; Fan, Jianqing; Wang, Yuyan
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Purdue University System; Purdue University; Princeton University; Fudan University
摘要：Factor modeling is an essential tool for exploring intrinsic dependence structures among high-dimensional random variables. Much progress has been made for estimating the covariance matrix from a high-dimensional factor model. However, the blessing of dimensionality has not yet been fully embraced in the literature: much of the available data are often ignored in constructing covariance matrix estimates. If our goal is to accurately estimate a covariance matrix of a set of targeted variables, ...
-
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...
