Journal of the American Statistical Association

最新文章

• Inference in Experiments With Matched Pairs AI翻译
  作者：Bai, Yuehao; Romano, Joseph P.; Shaikh, Azeem M.
  作者单位：University of Michigan System; University of Michigan; Stanford University; Stanford University; University of Chicago
  摘要：This article studies inference for the average treatment effect in randomized controlled trials where treatment status is determined according to a matched pairs design. By a matched pairs design, we mean that units are sampled iid from the population of interest, paired according to observed, baseline covariates and finally, within each pair, one unit is selected at random for treatment. This type of design is used routinely throughout the sciences, but fundamental questions about its implica...
• Consistent Sparse Deep Learning: Theory and Computation AI翻译
  作者：Sun, Yan; Song, Qifan; Liang, Faming
  作者单位：Purdue University System; Purdue University
  摘要：Deep learning has been the engine powering many successes of data science. However, the deep neural network (DNN), as the basic model of deep learning, is often excessively over-parameterized, causing many difficulties in training, prediction and interpretation. We propose a frequentist-like method for learning sparse DNNs and justify its consistency under the Bayesian framework: the proposed method could learn a sparse DNN with at most O(n/ log(n)) connections and nice theoretical guarantees ...
• Estimating Number of Factors by Adjusted Eigenvalues Thresholding AI翻译
  作者：Fan, Jianqing; Guo, Jianhua; Zheng, Shurong
  作者单位：Princeton University; Northeast Normal University - China; Northeast Normal University - China
  摘要：Determining the number of common factors is an important and practical topic in high-dimensional factor models. The existing literature is mainly based on the eigenvalues of the covariance matrix. Owing to the incomparability of the eigenvalues of the covariance matrix caused by the heterogeneous scales of the observed variables, it is not easy to find an accurate relationship between these eigenvalues and the number of common factors. To overcome this limitation, we appeal to the correlation ...
• Model-Free Feature Screening and FDR Control With Knockoff Features AI翻译
  作者：Liu, Wanjun; Ke, Yuan; Liu, Jingyuan; Li, Runze
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; University System of Georgia; University of Georgia; Xiamen University; Xiamen University
  摘要：This article proposes a model-free and data-adaptive feature screening method for ultrahigh-dimensional data. The proposed method is based on the projection correlation which measures the dependence between two random vectors. This projection correlation based method does not require specifying a regression model, and applies to data in the presence of heavy tails and multivariate responses. It enjoys both sure screening and rank consistency properties under weak assumptions. A two-step approa...
• A Multiple-Testing Procedure for High-Dimensional Mediation Hypotheses AI翻译
  作者：Dai, James Y.; Stanford, Janet L.; LeBlanc, Michael
  作者单位：Fred Hutchinson Cancer Center; University of Washington; University of Washington Seattle
  摘要：Mediation analysis is of rising interest in epidemiologic studies and clinical trials. Among existing methods, the joint significance test yields an overly conservative Type I error rate and low power, particularly for high-dimensional mediation hypotheses. In this article, we develop a multiple-testing procedure that accurately controls the family-wise error rate (FWER) and the false discovery rate (FDR) when testing high-dimensional mediation hypotheses. The core of our procedure is based on...
• A Mechanistic Model of Annual Sulfate Concentrations in the United States AI翻译
  作者：Wikle, Nathan B.; Hanks, Ephraim M.; Henneman, Lucas R. F.; Zigler, Corwin M.
  作者单位：University of Texas System; University of Texas Austin; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; George Mason University
  摘要：Understanding how individual pollution sources contribute to ambient sulfate pollution is critical for assessing past and future air quality regulations. Since attribution to specific sources is typically not encoded in spatial air pollution data, we develop a mechanistic model which we use to estimate, with uncertainty, the contribution of ambient sulfate concentrations attributable specifically to sulfur dioxide (SO2) emissions from individual coal-fired power plants in the central United St...
• Dynamic Stochastic Blockmodel Regression for Network Data: Application to International Militarized Conflicts AI翻译
  作者：Olivella, Santiago; Pratt, Tyler; Imai, Kosuke
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; Yale University; Harvard University; Harvard University
  摘要：The decision to engage in military conflict is shaped by many factors, including state- and dyad-level characteristics as well as the state's membership in geopolitical coalitions. Supporters of the democratic peace theory, for example, hypothesize that the community of democratic states is less likely to wage war with each other. Such theories explain the ways in which nodal and dyadic characteristics affect the evolution of conflict patterns over time via their effects on group memberships. ...
• Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction AI翻译
  作者：Fan, Jianqing; Masini, Ricardo; Medeiros, Marcelo C.
  作者单位：Princeton University; Princeton University; Getulio Vargas Foundation; Pontificia Universidade Catolica do Rio de Janeiro
  摘要：Optimal pricing, that is determining the price level that maximizes profit or revenue of a given product, is a vital task for the retail industry. To select such a quantity, one needs first to estimate the price elasticity from the product demand. Regression methods usually fail to recover such elasticities due to confounding effects and price endogeneity. Therefore, randomized experiments are typically required. However, elasticities can be highly heterogeneous depending on the location of st...
• Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-differentiable Priors AI翻译
  作者：Goldman, Jacob Vorstrup; Sell, Torben; Singh, Sumeetpal Sidhu
  作者单位：University of Cambridge; University of Cambridge
  摘要：The use of nondifferentiable priors in Bayesian statistics has become increasingly popular, in particular in Bayesian imaging analysis. Current state-of-the-art methods are approximate in the sense that they replace the posterior with a smooth approximation via Moreau-Yosida envelopes, and apply gradient-based discretized diffusions to sample from the resulting distribution. We characterize the error of the Moreau-Yosida approximation and propose a novel implementation using underdamped Langev...
• Survival Regression Models With Dependent Bayesian Nonparametric Priors AI翻译
  作者：Riva-Palacio, Alan; Leisen, Fabrizio; Griffin, Jim
  作者单位：Universidad Nacional Autonoma de Mexico; University of Nottingham; University of London; University College London
  摘要：We present a novel Bayesian nonparametric model for regression in survival analysis. Our model builds on the classical neutral to the right model of Doksum and on the Cox proportional hazards model of Kim and Lee. The use of a vector of dependent Bayesian nonparametric priors allows us to efficiently model the hazard as a function of covariates while allowing nonproportionality. The model can be seen as having competing latent risks. We characterize the posterior of the underlying dependent ve...