Journal of the American Statistical Association

最新文章

• A Latent Source Model to Detect Multiple Spatial Clusters With Application in a Mobile Sensor Network for Surveillance of Nuclear Materials AI翻译
  作者：Cheng, Jerry Q.; Xie, Minge; Chen, Rong; Roberts, Fred
  作者单位：Rutgers University System; Rutgers University New Brunswick; Rutgers University Biomedical & Health Sciences; Rutgers University System; Rutgers University New Brunswick; Rutgers University System; Rutgers University New Brunswick; Rutgers University System; Rutgers University New Brunswick
  摘要：Potential nuclear attacks are among the most devastating terrorist attacks, with severe loss of human lives as well as damage to infrastructure. To deter such threats, it becomes increasingly vital to have sophisticated nuclear surveillance and detection systems deployed in major cities in the United States, such as New York City. In this article, we design a mobile sensor network and develop statistical algorithms and models to provide consistent and pervasive surveillance of nuclear material...
• Efficiency for Regularization Parameter Selection in Penalized Likelihood Estimation Of Misspecified Models AI翻译
  作者：Flynn, Cheryl J.; Hurvich, Clifford M.; Simonoff, Jeffrey S.
  作者单位：New York University
  摘要：It has been shown that Akaike information criterion (AIC)-type criteria are asymptotically efficient selectors of the tuning parameter in nonconcave penalized regression methods under the assumption that the population variance is known or that a consistent estimator is available. We relax this assumption to prove that AIC itself is asymptotically efficient and we study its performance in finite samples. In classical regression, it is known that AIC tends to select overly complex models when t...
• Mediation and Spillover Effects in Group-Randomized Trials: A Case Study of the 4Rs Educational Intervention AI翻译
  作者：Vanderweele, Tyler J.; Hong, Guanglei; Jones, Stephanie M.; Brown, Joshua L.
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; University of Chicago; Harvard University; Fordham University
  摘要：Peer influence and social interactions can give rise to spillover effects in which the exposure of one individual may affect outcomes of other individuals. Even if the intervention under study occurs at the group or cluster level as in group-randomized trials, spillover effects can occur when the mediator of interest is measured at a lower level than the treatment. Evaluators who choose groups rather than individuals as experimental units in a randomized trial often anticipate that the desirab...
• Bayesian Inference for Logistic Models Using Polya-Gamma Latent Variables AI翻译
  作者：Polson, Nicholas G.; Scott, James G.; Windle, Jesse
  作者单位：University of Chicago; University of Texas System; University of Texas Austin; Duke University
  摘要：We propose a new data-augmentation strategy for fully Bayesian inference in models with binomial likelihoods. The approach appeals to a new class of Polya-Gamma distributions, which are constructed in detail. A variety of examples are presented to show the versatility of the method, including logistic regression, negative binomial regression, nonlinear mixed-effect models, and spatial models for count data. In each case, our data-augmentation strategy leads to simple, effective methods for pos...
• Nonparametric Mixture of Regression Models AI翻译
  作者：Huang, Mian; Li, Runze; Wang, Shaoli
  作者单位：Shanghai University of Finance & Economics; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：Motivated by an analysis of U.S. house price index (HPI) data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the asce...
• Simultaneous Grouping Pursuit and Feature Selection Over an Undirected Graph AI翻译
  作者：Zhu, Yunzhang; Shen, Xiaotong; Pan, Wei
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
  摘要：In high-dimensional regression, grouping pursuit and feature selection have their own merits while complementing each other in battling the curse of dimensionality. To seek a parsimonious model, we perform simultaneous grouping pursuit and feature selection over an arbitrary undirected graph with each node corresponding to one predictor. When the corresponding nodes are reachable from each other over the graph, regression coefficients can be grouped, whose absolute values are the same or close...
• A Unified Approach to Semiparametric Transformation Models Under General Biased Sampling Schemes AI翻译
  作者：Kim, Jane Paik; Lu, Wenbin; Sit, Tony; Ying, Zhiliang
  作者单位：Stanford University; North Carolina State University; Columbia University
  摘要：We propose a unified estimation method for semiparametric linear transformation models under general biased sampling schemes. The new estimator is obtained from a set of counting process-based unbiased estimating equations, developed through introducing a general weighting scheme that offsets the sampling bias. The usual asymptotic properties, including consistency and asymptotic normality, are established under suitable regularity conditions. A closed-form formula is derived for the limiting ...
• Extending the State-Space Model to Accommodate Missing Values in Responses and Covariates AI翻译
  作者：Naranjo, Arlene; Trindade, A. Alexandre; Casella, George
  作者单位：State University System of Florida; University of Florida; Texas Tech University System; Texas Tech University; State University System of Florida; University of Florida
  摘要：This article proposes an extended state-space model for accommodating multivariate panel data. The novel aspect of this contribution is an adjustment to the classical model for multiple subjects that allows missingness in the covariates in addition to the responses. Missing covariate data are handled by a second state-space model nested inside the first to represent unobserved exogenous information. Relevant Kalman filter equations are derived, and explicit expressions are provided for both th...
• Local Linear Regression on Manifolds and Its Geometric Interpretation AI翻译
  作者：Cheng, Ming-Yen; Wu, Hau-Tieng
  作者单位：National Taiwan University; University of California System; University of California Berkeley
  摘要：High-dimensional data analysis has been an active area, and the main focus areas have been variable selection and dimension reduction. In practice, it occurs often that the variables are located on an unknown, lower-dimensional nonlinear manifold. Under this manifold assumption, one purpose of this article is regression and gradient estimation on the manifold, and another is developing a new tool for manifold learning. As regards the first aim, we suggest directly reducing the dimensionality t...
• Markov-Modulated Nonhomogeneous Poisson Processes for Modeling Detections in Surveys of Marine Mammal Abundance AI翻译
  作者：Langrock, Roland; Borchers, David L.; Skaug, Hans J.
  作者单位：University of St Andrews; University of Bergen
  摘要：We consider Markov-modulated nonhomogeneous Poisson processes for modeling sightings of marine mammals in shipboard or aerial surveys. In such surveys, detection of an animal is possible only when it surfaces, and with some species a substantial proportion of animals is missed because they are diving and thus not available for detection. This needs to be adequately accounted for to avoid biased abundance estimates. The tendency of surfacing events of marine mammals to occur in clusters motivat...