Journal of the American Statistical Association

最新文章

• Discussion of Penalized Spline of Propensity Methods for Treatment Comparison by Zhou, Elliott, and Little AI翻译
  作者：Yang, Shu; Zeng, Donglin
  作者单位：North Carolina State University; University of North Carolina; University of North Carolina Chapel Hill
• Robust Alternatives to ANCOVA for Estimating the Treatment Effect via a Randomized Comparative Study AI翻译
  作者：Jiang, Fei; Tian, Lu; Fu, Haoda; Hasegawa, Takahiro; Wei, L. J.
  作者单位：University of Hong Kong; Stanford University; Eli Lilly; Shionogi & Company Limited; Harvard University
  摘要：In comparing two treatments via a randomized clinical trial, the analysis of covariance (ANCOVA) technique is often utilized to estimate an overall treatment effect. The ANCOVA is generally perceived as a more efficient procedure than its simple two sample estimation counterpart. Unfortunately, when the ANCOVA model is nonlinear, the resulting estimator is generally not consistent. Recently, various nonparametric alternatives to the ANCOVA, such as the augmentation methods, have been proposed ...
• Minimax Estimation of the Volume of a Set Under the Rolling Ball Condition AI翻译
  作者：Arias-Castro, Ery; Pateiro-Lopez, Beatriz; Rodriguez-Casal, Alberto
  作者单位：University of California System; University of California San Diego; Universidade de Santiago de Compostela
  摘要：We consider the problem of estimating the volume of a compact domain in a Euclidean space based on a uniform sample from the domain. We assume that the domain has a boundary with positive reach. We propose a data-splitting approach to correct the bias of the plug-in estimator based on the sample alpha-convex hull. We show that this simple estimator achieves a minimax lower bound that we derive. Some numerical experiments corroborate our theoretical findings. Supplementary materials for this ar...
• Graph-Guided Banding of the Covariance Matrix AI翻译
  作者：Bien, Jacob
  作者单位：University of Southern California
  摘要：Regularization has become a primary tool for developing reliable estimators of the covariance matrix in high-dimensional settings. To curb the curse of dimensionality, numerous methods assume that the population covariance (or inverse covariance) matrix is sparse, while making no particular structural assumptions on the desired pattern of sparsity. A highly-related, yet complementary, literature studies the specific setting in which the measured variables have a known ordering, in which case a...
• Bayesian Semiparametric Functional Mixed Models for Serially Correlated Functional Data, With Application to Glaucoma Data AI翻译
  作者：Lee, Wonyul; Miranda, Michelle F.; Rausch, Philip; Baladandayuthapani, Veerabhadran; Fazio, Massimo; Downs, J. Crawford; Morris, Jeffrey S.
  作者单位：University of Texas System; UTMD Anderson Cancer Center; Humboldt University of Berlin; University of Alabama System; University of Alabama Birmingham
  摘要：Glaucoma, a leading cause of blindness, is characterized by optic nerve damage related to intraocular pressure (IOP), but its full etiology is unknown. Researchers at UAB have devised a custom device to measure scleral strain continuously around the eye under fixed levels of IOP, which here is used to assess how strain varies around the posterior pole, with IOP, and across glaucoma risk factors such as age. The hypothesis is that scleral strain decreases with age, which could alter biomechanic...
• A Computational Framework for Multivariate Convex Regression and Its Variants AI翻译
  作者：Mazumder, Rahul; Choudhury, Arkopal; Iyengar, Garud; Sen, Bodhisattva
  作者单位：Massachusetts Institute of Technology (MIT); University of North Carolina; University of North Carolina Chapel Hill; Columbia University; Columbia University
  摘要：We study the nonparametric least squares estimator (LSE) of a multivariate convex regression function. The LSE, given as the solution to a quadratic program with O(n(2)) linear constraints (n being the sample size), is difficult to compute for large problems. Exploiting problem specific structure, we propose a scalable algorithmic framework based on the augmented Lagrangian method to compute the LSE. We develop a novel approach to obtain smooth convex approximations to the fitted (piecewise af...
• FreSpeD: Frequency-Specific Change-Point Detection in Epileptic Seizure Multi-Channel EEG Data AI翻译
  作者：Schroder, Anna Louise; Ombao, Hernando
  作者单位：University of London; London School Economics & Political Science; King Abdullah University of Science & Technology
  摘要：The goal in this article is to develop a practical tool that identifies changes in the brain activity as recorded in electroencephalograms (EEG). Our method is devised to detect possibly subtle disruptions in normal brain functioning that precede the onset of an epileptic seizure. Moreover, it is able to capture the evolution of seizure spread from one region (or channel) to another. The proposed frequency-specific change-point detection method (FreSpeD) deploys a cumulative sum-type test stat...
• Discussion: A Spatial Modeling Approach for Linguistic Object Data: Analysing Dialect Sound Variations Across Great Britain, by Shahin Tavakoli et al AI翻译
  作者：Marron, J. S.
  作者单位：University of North Carolina; University of North Carolina Chapel Hill
• Estimating and Testing Vaccine Sieve Effects Using Machine Learning AI翻译
  作者：Benkeser, David; Gilbert, Peter B.; Carone, Marco
  作者单位：Emory University; Fred Hutchinson Cancer Center; Fred Hutchinson Cancer Center; University of Washington; University of Washington Seattle
  摘要：When available, vaccines are an effective means of disease prevention. Unfortunately, efficacious vaccines have not yet been developed for several major infectious diseases, including HIV and malaria. Vaccine sieve analysis studies whether and how the efficacy of a vaccine varies with the genetics of the pathogen of interest, which can guide subsequent vaccine development and deployment. In sieve analyses, the effect of the vaccine on the cumulative incidence corresponding to each of several p...
• Comment on Blessings of Multiple Causes AI翻译
  作者：Ogburn, Elizabeth L.; Shpitser, Ilya; Tchetgen, Eric J. Tchetgen
  作者单位：Johns Hopkins University; Johns Hopkins University; University of Pennsylvania