Journal of the American Statistical Association

最新文章

• Variable Selection in Nonparametric Classification Via Measurement Error Model Selection Likelihoods AI翻译
  作者：Stefanski, L. A.; Wu, Yichao; White, Kyle
  作者单位：North Carolina State University
  摘要：Using the relationships among ridge regression, LASSO estimation, and measurement error attenuation as motivation, a new measurement-error-model-based approach to variable selection is developed. After describing the approach in the familiar context of linear regression, we apply it to the problem of variable selection in nonparametric classification, resulting in a new kernel-based classifier with LASSO-like shrinkage and variable-selection properties. Finite-sample performance of the new cla...
• Dimension-Reduced Modeling of Spatio-Temporal Processes AI翻译
  作者：Brynjarsdottir, Jenny; Berliner, L. Mark
  作者单位：University System of Ohio; Case Western Reserve University; University System of Ohio; Ohio State University
  摘要：The field of spatial and spatio-temporal statistics is increasingly faced with the challenge of very large datasets. The classical approach to spatial and spatio-temporal modeling is very computationally demanding when datasets are large, which has led to interest in methods that use dimension-reduction techniques. In this article, we focus on modeling of two spatio-temporal processes where the primary goal is to predict one process from the other and where datasets for both processes are larg...
• Combining Dynamic Predictions From Joint Models for Longitudinal and Time-to-Event Data Using Bayesian Model Averaging AI翻译
  作者：Rizopoulos, Dimitris; Hatfield, Laura A.; Carlin, Bradley P.; Takkenberg, Johanna J. M.
  作者单位：Erasmus University Rotterdam; Erasmus MC; Harvard University; University of Minnesota System; University of Minnesota Twin Cities; Erasmus University Rotterdam; Erasmus MC
  摘要：The joint modeling of longitudinal and time-to-event data is an active area of statistics research that has received a lot of attention in recent years. More recently, a new and attractive application of this type of model has been to obtain individualized predictions of survival probabilities and/or of future longitudinal responses. The advantageous feature of these predictions is that they are dynamically updated as extra longitudinal responses are collected for the subjects of interest, pro...
• Detection of Unusual Increases in MRI Lesion Counts in Individual Multiple Sclerosis Patients AI翻译
  作者：Zhao, Yinshan; Li, David K. B.; Petkau, A. John; Riddehough, Andrew; Traboulsee, Anthony
  作者单位：University of British Columbia; University of British Columbia; University of British Columbia; University of British Columbia
  摘要：Data Safety and Monitoring Boards (DSMBs) for multiple sclerosis clinical trials consider an increase of contrast-enhancing lesions on repeated magnetic resonance imaging an indicator for potential adverse events. However, there are no published studies that clearly identify what should be considered an unexpected increase of lesion activity for a patient. To address this problem, we consider as an index the likelihood of observing lesion counts as large as those observed on the recent scans o...
• Exact Meta-Analysis Approach for Discrete Data and its Application to 2 x 2 Tables With Rare Events AI翻译
  作者：Liu, Dungang; Liu, Regina Y.; Xie, Min-ge
  作者单位：University System of Ohio; University of Cincinnati; Rutgers University System; Rutgers University New Brunswick
  摘要：This article proposes a general exact meta-analysis approach for synthesizing inferences from multiple studies of discrete data. The approach combines the p-value functions (also known as significance functions) associated with the exact tests from individual studies. It encompasses a broad class of exact meta-analysis methods, as it permits broad choices for the combining elements, such as tests used in individual studies, and any parameter of interest. The approach yields statements that exp...
• Filtering With Heavy Tails AI翻译
  作者：Harvey, Andrew; Luati, Alessandra
  作者单位：University of Cambridge; University of Bologna
  摘要：An unobserved components model in which the signal is buried in noise that is non-Gaussian may throw up observations that, when judged by the Gaussian yardstick, are outliers. We describe an observation-driven model, based on a conditional Student's t-distribution, which is tractable and retains some of the desirable features of the linear Gaussian model. Letting the dynamics be driven by the score of the conditional distribution leads to a specification that is not only easy to implement, but...
• Inference From Intrinsic Bayes' Procedures Under Model Selection and Uncertainty AI翻译
  作者：Womack, Andrew J.; Leon-Novelo, Luis; Casella, George
  作者单位：Indiana University System; Indiana University Bloomington; State University System of Florida; University of Florida; University of Louisiana Lafayette
  摘要：In this article, we present a fully coherent and consistent objective Bayesian analysis of the linear regression model using intrinsic priors. The intrinsic prior is a scaled mixture of g-priors and promotes shrinkage toward the subspace defined by a base (or null) model. While it has been established that the intrinsic prior provides consistent model selectors across a range of models, the posterior distribution of the model parameters has not previously been investigated. We prove that the p...
• Bayesian Forecasting of Cohort Fertility AI翻译
  作者：Schmertmann, Carl; Zagheni, Emilio; Goldstein, Joshua R.; Myrskylae, Mikko
  作者单位：State University System of Florida; Florida State University; City University of New York (CUNY) System; Queens College NY (CUNY); University of California System; University of California Berkeley; University of London; London School Economics & Political Science
  摘要：There are signs that fertility in rich countries may have stopped declining, but this depends critically on whether women currently in reproductive ages are postponing or reducing lifetime fertility. Analysis of average completed family sizes requires forecasts of remaining fertility for women born 1970-1995. We propose a Bayesian model for fertility that incorporates a priori information about patterns over age and time. We use a new dataset, the Human Fertility Database (HFD), to construct i...
• A Generic Path Algorithm for Regularized Statistical Estimation AI翻译
  作者：Zhou, Hua; Wu, Yichao
  作者单位：North Carolina State University
  摘要：Regularization is widely used in statistics and machine learning to prevent overfitting and gear solution toward prior information. In general, a regularized estimation problem minimizes the sum of a loss function and a penalty term. The penalty term is usually weighted by a tuning parameter and encourages certain constraints on the parameters to be estimated. Particular choices of constraints lead to the popular lasso, fused-lasso, and other generalized l(1) penalized regression methods. In t...
• Bayes Variable Selection in Semiparametric Linear Models AI翻译
  作者：Kundu, Suprateek; Dunson, David B.
  作者单位：Texas A&M University System; Texas A&M University College Station; Duke University
  摘要：There is a rich literature on Bayesian variable selection for parametric models. Our focus is on generalizing methods and asymptotic theory established for mixtures of g-priors to semiparametric linear regression models having unknown residual densities. Using a Dirichlet process location mixture for the residual density, we propose a semiparametric g-prior which incorporates an unknown matrix of cluster allocation indicators. For this class of priors, posterior computation can proceed via a s...