Established in 1888 and published quarterly in March, June, September, and December, the Journal of the American Statistical Association ( JASA ) has long been considered the premier journal of statistical science. Articles focus on statistical applications, theory, and methods throughout all disciplines that make use of data, including economic, social, biological, physical, engineering, and health sciences and the humanities.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; Duke University
作者：Bhattacharya, Anirban; Pati, Debdeep; Pillai, Natesh S.; Dunson, David B.
作者单位：Texas A&M University System; Texas A&M University College Station; State University System of Florida; Florida State University; Harvard University; Duke University
摘要：Penalized regression methods, such as L-1 regularization, are routinely used in high-dimensional applications, and there is a rich literature on optimality properties under sparsity assumptions. In the Bayesian paradigm, sparsity is routinely induced through two-component mixture priors having a probability mass at zero, but such priors encounter daunting computational problems in high dimensions. This has motivated continuous shrinkage priors, which can be expressed as global-local scale mixt...
摘要：This article investigates marginal screening for detecting the presence of significant predictors in high-dimensional regression. Screening large numbers of predictors is a challenging problem due to the nonstandard limiting behavior of post-model-selected estimators. There is a common misconception that the oracle property for such estimators is a panacea, but the oracle property only holds away from the null hypothesis of interest in marginal screening. To address this difficulty, we propose...
作者单位：University of Kent; University of Cambridge; University of Cambridge
摘要：Characterizing the brain source activity using magnetoencephalography (MEG) requires solving an ill-posed inverse problem. Most source reconstruction procedures are performed in terms of power comparison. However, in the presence of voxel-specific noises, the direct power analysis can be misleading due to the power distortion as suggested by our multiple trial MEG study on a face-perception experiment. To tackle the issue, we propose a temporal autocorrelation-based method for the above analys...
摘要：We demonstrate how many classical rank tests, such as the Wilcoxon Mann Whitney, Kruskal Wallis, and Friedman test, can be embedded in a statistical modeling framework and how the method can be used to construct new rank tests. In addition to hypothesis testing, the method allows for estimating effect sizes with an informative interpretation, resulting in a better understanding of the data. Supplementary materials for this article are available online.
摘要：Marginal structural models (MSMs) are becoming increasingly popular as a tool for causal inference from longitudinal data. Unlike standard regression models, MSMs can adjust for time-dependent observed confounders while avoiding the bias due to the direct adjustment for covariates affected by the treatment. Despite their theoretical appeal, a main practical difficulty of MSMs is the required estimation of inverse probability weights. Previous studies have found that MSMs can be highly sensitiv...
作者单位：Otto von Guericke University; Helmholtz Association; Karlsruhe Institute of Technology; University of California System; University of California Irvine
摘要：The primary contributions of this article are rigorously developed novel statistical methods for detecting change points in multivariate time series. We extend the class of score type change point statistics considered in 2007 by Huskova, Praskova, and Steinebach to the vector autoregressive (VAR) case and the epidemic change alternative. Our proposed procedures do not require the observed time series to actually follow the VAR model. Instead, following the strategy implicitly employed by prac...
