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作者：Ma, Y; Chiou, JM; Wang, N
作者单位：Texas A&M University System; Texas A&M University College Station; Academia Sinica - Taiwan
摘要：We study the heteroscedastic partially linear model with an unspecified partial baseline component and a nonparametric variance function. An interesting finding is that the performance of a naive weighted version of the existing estimator could deteriorate when the smooth baseline component is badly estimated. To avoid this, we propose a family of consistent estimators and investigate their asymptotic properties. We show that the optimal semiparametric efficiency bound can be reached by a semi...
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作者：Houseman, E. Andres; Coull, Brent A.; Ryan, Louise M.
作者单位：Harvard University; Harvard T.H. Chan School of Public Health
摘要：In this paper we present an easy-to-implement graphical distribution diagnostic for linear models with correlated errors. Houseman et al. (2004) constructed quantile-quantile plots for the marginal residuals of such models, suitably transformed. We extend the pointwise asymptotic theory to address the global stochastic behaviour of the corresponding empirical cumulative distribution function, and describe a simulation technique that serves as a computationally efficient parametric bootstrap fo...
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作者：Gorfine, Malka; Zucker, David M.; Hsu, Li
作者单位：Technion Israel Institute of Technology; Hebrew University of Jerusalem; Fred Hutchinson Cancer Center
摘要：We provide a simple estimation procedure for a general frailty model for the analysis of prospective correlated failure times. The large-sample properties of the proposed estimators of both the regression coefficient vector and the dependence parameter are described, and consistent variance estimators are given. A brief outline of the proofs is given. In a simulation study under the widely used gamma frailty model, our proposed approach was found to have essentially the same efficiency as the ...
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作者：Huang, XZ; Stefanski, LA; Davidian, M
作者单位：North Carolina State University
摘要：We present methods for diagnosing the effects of model misspecification of the true-predictor distribution in structural measurement error models. We first formulate latent-model robustness theoretically. Then we provide practical techniques for examining the adequacy of an assumed latent predictor model. The methods are illustrated via analytical examples, application to simulated data and with data from a study of coronary heart disease.
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作者：Matsuda, Yasumasa
作者单位：Tohoku University
摘要：A graphical model for multivariate time series is a concept extended by Dahlhaus (2000) from that for a random vector to a multivariate time series. We propose a test statistic for identifying the model based on the Kullback-Leibler divergence between two graphical models. The null distribution is shown to be asymptotically normal with mean and variance which depend just on the dimensions of the graphs.
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作者：Lin, CT; Wu, JS; Yen, CH
作者单位：Tamkang University
摘要：Jones (1989) has pointed out that piecewise linear interpolated kernel density estimators on a sufficiently fine grid can be visually indistinguishable from the true density. A simple device, the kernel polygon, is proposed for eliminating the evaluation of the normalisation constant of the estimator while retaining its property of being a density function as well as providing practical advantages. The class of uniform and linear kernels of the kernel polygons is given. Finally, we present a s...
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作者：Guttorp, Peter; Gneiting, Tilmann
作者单位：University of Washington; University of Washington Seattle
摘要：Handcock & Stein (1993) introduced the Matern family of spatial correlations into statistics as a flexible parametric class with one parameter determining the smoothness of the paths of the underlying spatial field. We document the varied history of this family, which includes contributions by eminent physical scientists and statisticians.
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作者：Lee, Yoonkyung; Kim, Yuwon; Lee, Sangjun; Koo, Ja-Yong
作者单位：University System of Ohio; Ohio State University; Seoul National University (SNU); Seoul National University (SNU); Korea University
摘要：The support vector machine has been a popular choice of classification method for many applications in machine learning. While it often outperforms other methods in terms of classification accuracy, the implicit nature of its solution renders the support vector machine less attractive in providing insights into the relationship between covariates and classes. Use of structured kernels can remedy the drawback. Borrowing the flexible model-building idea of functional analysis of variance decompo...
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作者：Kim, Sinae; Tadesse, Mahlet G.; Vannucci, Marina
作者单位：Texas A&M University System; Texas A&M University College Station; University of Pennsylvania; Texas A&M University System; Texas A&M University College Station
摘要：The increased collection of high-dimensional data in various fields has raised a strong interest in clustering algorithms and variable selection procedures. In this paper, we propose a model-based method that addresses the two problems simultaneously. We introduce a latent binary vector to identify discriminating variables and use Dirichlet process mixture models to define the cluster structure. We update the variable selection index using a Metropolis algorithm and obtain inference on the clu...
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作者：Tchetgen, Eric J.; Coull, Brent A.
作者单位：Harvard University; Harvard T.H. Chan School of Public Health
摘要：We introduce a diagnostic test for the mixing distribution in a generalised linear mixed model. The test is based on the difference between the marginal maximum likelihood and conditional maximum likelihood estimators of a subset of the fixed effects in the model. We derive the asymptotic variance of this difference, and propose a test statistic that has a limiting chi-squared distribution under the null hypothesis that the mixing distribution is correctly specified. This strategy uses an idea...
