Journal of the American Statistical Association

最新文章

• Regularization of wavelet approximations - Discussion AI翻译
  作者：Moulin, P
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign
• Robust inference for generalized linear models AI翻译
  作者：Cantoni, E; Ronchetti, E
  作者单位：University of Geneva
  摘要：By starting from a natural class of robust estimators for generalized linear models based on the notion of qua-si-likelihood, we define robust deviances that can be used for stepwise model selection as in the classical framework. Wc derive the asymptotic distribution of tests based on robust deviances, and we investigate the stability of their asymptotic level under contamination. The binomial and Poisson models are treated in detail. Two applications to real data and a sensitivity analysis sh...
• Inference for density families using functional principal component analysis - Comment AI翻译
  作者：Ramsay, JO
  作者单位：McGill University
• A marginal model for analyzing discrete outcomes from longitudinal surveys with outcomes subject to multiple-cause nonresponse AI翻译
  作者：Miller, ME; Ten Have, TR; Reboussin, BA; Lohman, KK; Rejeski, WJ
  作者单位：Wake Forest University; Wake Forest Baptist Medical Center; University of Pennsylvania; Wake Forest University; Wake Forest Baptist Medical Center; Wake Forest University
  摘要：Techniques for analyzing categorical outcomes obtained from longitudinal survey samples, with outcomes subject to multiple-cause nonresponse, are developed within the framework, of weighted generalized estimating equations. Development of these techniques was motivated by disability data obtained from the Longitudinal Study of Aging (LSOA), a longitudinal survey sample containing missing follow-up for many elderly participants. We posit a model that combines different multivariate link functio...
• Inference for density families using functional principal component analysis AI翻译
  作者：Kneip, A; Utikal, KJ
  作者单位：Johannes Gutenberg University of Mainz
  摘要：We consider t = 1,..., T samples of lid observations {X-1t,...,X-ntt} from unknown population densities {f(t)}. To characterize differences and similarities of {f(t)}, we assume their expansions into the first L principal components. From the given observations {X-it}, we study inference on the components and on their required number L. A detailed asymptotic theory is presented. Our method is applied in the analysis of yearly cross-sectional samples of British households. Interpretation of the...
• Bayesian and conditional frequentist testing of a parametric model versus nonparametric alternatives AI翻译
  作者：Berger, JO; Guglielmi, A
  作者单位：Duke University; Consiglio Nazionale delle Ricerche (CNR)
  摘要：Testing the fit of data to a parametric model can be done by embedding the parametric model in a nonparametric alternative and computing the Bayes factor of the parametric model to the nonparametric alternative. Doing so by specifying the nonparametric alternative via a Polya tree process is particularly attractive, from both theoretical and methodological perspectives. Among the benefits is a degree of computational simplicity that even allows for robustness analyses to be implemented Default...
• A note on the efficiency of sandwich covariance matrix estimation AI翻译
  作者：Kauermann, G; Carroll, RJ
  作者单位：University of Glasgow; University of Glasgow; Texas A&M University System; Texas A&M University College Station
  摘要：The sandwich estimator, also known as robust covariance matrix estimator, heteroscedasticity-consistent covariance matrix estimate, or empirical covariance matrix estimator, has achieved increasing use in the econometric literature as well as with the growing popularity of generalized estimating equations. Its virtue is that it provides consistent estimates of the covariance matrix for parameter estimates even when the fitted parametric model fails to hold or is not even specified. Surprisingl...
• Estimation of the head sensitivity function in scanning magnetoresistance microscopy AI翻译
  作者：Higdon, D; Yamamoto, S
  作者单位：Duke University
  摘要：We apply Bayesian image analysis techniques to a problem in a newly developed scanned probe technology that uses commercial magnetoresistive (MR) record and playback heads as probes to sense magnetic fields. This technology can be used for magnetic imaging and for evaluating playback and record processes in magnetic recording. In MR microscopy, an MR head is raster scanned while in physical contact with a magnetic sample (e.g., hard disk media, tape, or fine magnetic particles). By plotting th...
• Stochastic neural networks with applications to nonlinear time series AI翻译
  作者：Lai, TL; Wong, SPS
  作者单位：Stanford University; Hong Kong University of Science & Technology
  摘要：we consider a variant of the conventional neural network model, called the stochastic neural network, that can be used to approximate complex nonlinear stochastic systems. We show how the expectation-maximization algorithm can be used to develop efficient estimation schemes that have much lower computational complexity than those for conventional neural networks. This enables us to carry out model selection procedures, such as the Bayesian information criterion, to choose the number of hidden ...
• Vote tampering in a district justice election in Beaver County, PA AI翻译
  作者：DiMatteo, I; Kadane, JB
  作者单位：Carnegie Mellon University
  摘要：This article examines the evidence of vote tampering in a District Justice election in Beaver County, Pennsylvania. An informal exploratory data analysis and a legal history are followed by a formal Bayesian model of the data from the vote count on election night and the recount completed 2 months later. The evidence suggests that persons unknown could have gained access to the boxes containing the paper ballots. and surprising patterns of changes in the counts support the inference that certa...