Journal of the American Statistical Association

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• Learning Sparse Causal Gaussian Networks With Experimental Intervention: Regularization and Coordinate Descent AI翻译
  作者：Fu, Fei; Zhou, Qing
  作者单位：University of California System; University of California Los Angeles
  摘要：Causal networks are graphically represented by directed acyclic graphs (DAGs). Learning causal networks from data is a challenging problem due to the size of the space of DAGs, the acyclicity constraint placed on the graphical structures, and the presence of equivalence classes. In this article, we develop an L-1-penalized likelihood approach to estimate the structure of causal Gaussian networks. A blockwise coordinate descent algorithm, which takes advantage of the acyclicity constraint, is p...
• A Bayesian Procedure for File Linking to Analyze End-of-Life Medical Costs AI翻译
  作者：Gutman, Roee; Afendulis, Christopher C.; Zaslavsky, Alan M.
  作者单位：Brown University; Harvard University; Harvard Medical School
  摘要：End-of-life medical expenses are a significant proportion of all health care expenditures. These costs were studied using costs of services from Medicare claims and cause of death (CoD) from death certificates. In the absence of a unique identifier linking the two datasets, common variables identified unique matches for only 33% of deaths. The remaining cases formed cells with multiple cases (32% in cells with an equal number of cases from each file and 35% in cells with an unequal number). We...
• Inferential Models: A Framework for Prior-Free Posterior Probabilistic Inference AI翻译
  作者：Martin, Ryan; Liu, Chuanhai
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Purdue University System; Purdue University
  摘要：Posterior probabilistic statistical inference without priors is an important but so far elusive goal. Fisher's fiducial inference, Dempster-Shafer theory of belief functions, and Bayesian inference with default priors are attempts to achieve this goal but, to date, none has given a completely satisfactory picture. This article presents a new framework for probabilistic inference, based on inferential models (IMs), which not only provides data-dependent probabilistic measures of uncertainty abo...
• Discovering Findings That Replicate From a Primary Study of High Dimension to a Follow-Up Study AI翻译
  作者：Bogomolov, Marina; Heller, Ruth
  作者单位：Technion Israel Institute of Technology; Tel Aviv University
  摘要：We consider the problem of identifying whether findings replicate from one study of high dimension to another, when the primary study guides the selection of hypotheses to be examined in the follow-up study as well as when there is no division of roles into the primary and the follow-up study. We show that existing meta-analysis methods are not appropriate for this problem, and suggest novel methods instead. We prove that our multiple testing procedures control for appropriate error rates. The...
• Multinomial Inverse Regression for Text Analysis Comment AI翻译
  作者：Blei, David M.
  作者单位：Princeton University
• Multinomial Inverse Regression for Text Analysis Comment AI翻译
  作者：Grimmer, Justin
  作者单位：Stanford University
• Rejoinder: Efficiency and Structure in MNIR AI翻译
  作者：Taddy, Matt
  作者单位：University of Chicago
• Nonparametric Identification of Copula Structures AI翻译
  作者：Li, Bo; Genton, Marc G.
  作者单位：Purdue University System; Purdue University; King Abdullah University of Science & Technology
  摘要：We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric and based on the asymptotic distribution of the empirical copula process. We perform simulation experiments to evaluate our test and conclude that our method is reliable and powerful for assessing common assumptions on the structure of copulas, particu...
• A Hierarchical Bayesian Approach for Aerosol Retrieval Using MISR Data AI翻译
  作者：Wang, Yueqing; Jiang, Xin; Yu, Bin; Jiang, Ming
  作者单位：University of California System; University of California Berkeley; Peking University; University of California System; University of California Berkeley
  摘要：Atmospheric aerosols can cause serious damage to human health and reduce life expectancy. Using the radiances observed by NASA's Multi-angle Imaging SpectroRadiometer (MISR), the current MISR operational algorithm retrieves aerosol optical depth (AOD) at 17.6 km resolution. A systematic study of aerosols and their impact on public health, especially in highly populated urban areas, requires finer-resolution estimates of AOD's spatial distribution. We embed MISR's operational weighted least squ...
• Ensemble Subsampling for Imbalanced Multivariate Two-Sample Tests AI翻译
  作者：Chen, Lisha; Dou, Winston Wei; Qiao, Zhihua
  作者单位：Yale University; Massachusetts Institute of Technology (MIT); JP Morgan Chase & Company
  摘要：Some existing nonparametric two-sample tests for equality of multivariate distributions perform unsatisfactorily when the two sample sizes are unbalanced. In particular, the power of these tests tends to diminish with increasingly unbalanced sample sizes. In this article, we propose a new testing procedure to solve this problem. The proposed test, based on the nearest neighbor method by Schilling, employs a novel ensemble subsampling scheme to remedy this issue. More specifically, the test sta...