Journal of the American Statistical Association

最新文章

• Semiparametric estimation of spectral density with irregular observations AI翻译
  作者：Im, Hae Kyung; Stein, Michael L.; Zhu, Zhengyuan
  作者单位：University of Chicago; University of Chicago; University of North Carolina; University of North Carolina Chapel Hill
  摘要：We propose a semiparametric method for estimating spectral densities of isotropic Gaussian processes with scattered data. The spectral density function (Fourier transform of the covariance function) is modeled as a linear combination of B-splines up to a cutoff frequency and, from this point, a truncated algebraic tail. We calculate an analytic expression for the covariance function and tackle several numerical issues that arise when calculating the likelihood. The parameters are estimated by ...
• A nonparametric assessment of properties of space-time covariance functions AI翻译
  作者：Li, Bo; Genton, Marc G.; Sherman, Michael
  作者单位：National Center Atmospheric Research (NCAR) - USA; University of Geneva; Texas A&M University System; Texas A&M University College Station
  摘要：We propose a unified framework for testing various assumptions commonly made for covariance functions of stationary spatio-temporal random fields. The methodology is based on the asymptotic normality of space-time covariance estimators. We focus on tests for full symmetry and separability in this article, but our framework naturally covers testing for isotropy and Taylor's hypothesis. Our test successfully detects the asymmetric and nonseparable features in two sets of wind speed data. We per-...
• Rejoinder AI翻译
  作者：Rappold, Ana Grohovac; Lavine, Michael; Lozier, Susan
  作者单位：United States Environmental Protection Agency; Duke University; Duke University; Duke University
• Determining the number of factors in the general dynamic factor model AI翻译
  作者：Hallin, Marc; Liska, Roman
  作者单位：Universite Libre de Bruxelles; Universite Libre de Bruxelles; Universite Libre de Bruxelles
  摘要：This article develops an information criterion for determining the number q of common shocks in the general dynamic factor model developed by Form et al., as opposed to the restricted dynamic model considered by Bai and Ng and by Amengual and Watson. Our criterion is based on the fact that this number q is also the number of diverging eigenvalues of the spectral density matrix of the observations as the number n of series goes to infinity. We provide sufficient conditions for consistency of th...
• Partial linear regression models for clustered data AI翻译
  作者：Chen, K; Jin, ZZ
  作者单位：Hong Kong University of Science & Technology; Columbia University
  摘要：This article considers the analysis of clustered data via partial linear regression models. Adopting the idea of modeling the within-cluster correlation from the method of generalized estimating equations, a least squares type estimate of the slope parameter is obtained through piecewise local polynomial approximation of the nonparametric component. This slope estimate has several advantages: (a) It attains n(1/2)-consistency without undersmoothing; (b) it is efficient when correct within-clus...
• High-breakdown inference for mixed linear models AI翻译
  作者：Copt, S; Victoria-Feser, MP
  作者单位：University of Sydney; University of Geneva
  摘要：Mixed linear models are used to analyze data in many settings. These models have a multivariate normal formulation in most cases. The maximum likelihood estimator (MLE) or the residual MLE (REML) is usually chosen to estimate the parameters. However, the latter are based on the strong assumption of exact multivariate normality. Welsh and Richardson have shown that these estimators are not robust to small deviations from multivariate normality. This means that in practice a small proportion of ...
• Estimation of finite population domain means: A model-assisted empirical best prediction approach AI翻译
  作者：Jiang, JM; Lahiri, R
  作者单位：University of California System; University of California Davis; University System of Maryland; University of Maryland College Park
  摘要：In this article we introduce a general methodology for producing a model-assisted empirical best predictor (EBP) of a finite population domain mean using data from a complex survey. Our method improves on the commonly used design-consistent survey estimator by using a suitable mixed model. Such a model combines information from related sources, such as census and administrative data. Unlike a purely model-based EBP, the proposed model-assisted EBP converges in probability to the customary desi...
• Clustering categorical data based on distance vectors AI翻译
  作者：Zhang, P; Wang, XG; Song, PXK
  作者单位：University of Waterloo; York University - Canada
  摘要：We introduce a novel statistical procedure for clustering categorical data based on Hamming distance (HD) vectors. The proposed method is conceptually simple and computationally straightforward, because it does not require any specific statistical models or any convergence criteria. Moreover, unlike most currently existing algorithms that compute the class membership or membership probability for every data point at each iteration, our algorithm sequentially extracts clusters from the given da...
• Variable selection for model-based clustering AI翻译
  作者：Raftery, AE; Dean, N
  作者单位：University of Washington; University of Washington Seattle
  摘要：We consider the problem of variable or feature selection for model-based clustering. The problem of comparing two nested subsets of variables is recast as a model comparison problem and addressed using approximate Bayes factors. A greedy search algorithm is proposed for finding a local optimum in model space. The resulting method selects variables (or features), the number of clusters, and the clustering model simultaneously. We applied the method to several simulated and real examples and fou...
• Hidden Markov models for microarray time course data in multiple biological conditions - Discussion AI翻译
  作者：Li, Hongzhe; Hong, Fangxin
  作者单位：University of Pennsylvania; Salk Institute