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作者：Smith, Richard L.
作者单位：University of North Carolina; University of North Carolina Chapel Hill
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作者：Cheng, Philip E.; Liou, Michelle; Aston, John A. D.
作者单位：Academia Sinica - Taiwan; University of Warwick
摘要：Likelihood ratio (LR) tests for association and for interaction are examined for three-way contingency tables, particularly the widely used 2 x 2 x K table. Mutual information identities are used to characterize the information decomposition and the logical relationship between the omnibus LR test for conditional independence across K strata and its two independent components. LR tests for interaction and for uniform association. The latter two tests are logically connected to formulating a na...
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作者：McCormick, Tyler H.; Salganik, Matthew J.; Zheng, Tian
作者单位：Columbia University; Princeton University; Princeton University
摘要：In this article we develop a method to estimate both individual social network size (ie, degree) and die distribution of network sizes in a population by asking respondents how many people they know in specific subpopulations (c g people named Michael) Building on the scale-up method of Killworth ei al (1998b) and other previous attempts to estimate individual network size we propose a latent non-random mixing model which resolves three known problems with previous approaches As a byproduct ou...
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作者：Lele, Subhash R.; Nadeem, Khurram; Schmuland, Byron
作者单位：University of Alberta
摘要：Maximum likelihood estimation for Generalized Linear Mixed Models (GLMM), an important class of statistical models with substantial applications in epidemiology, medical statistics, and many other fields, poses significant computational difficulties. In this article, we use data cloning, a simple computational method that exploits advances in Bayesian computation, in particular the Markov Chain Monte Carlo method, to obtain maximum likelihood estimators of the parameters in these models. This ...
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作者：Radchenko, Peter; James, Gareth M.
作者单位：University of Southern California
摘要：Numerous penalization based methods have been proposed for fitting a traditional linear regression model in which the number of predictors, p, is large relative to the number of observations, n. Most of these approaches assume sparsity in the underlying coefficients and perform some form of variable selection. Recently, some of this work has been extended to nonlinear additive regression models. However, in many contexts one wishes to allow for the possibility of interactions among the predict...
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作者：Li, Fan; Zhang, Nancy R.
作者单位：Duke University; Stanford University
摘要：We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate space is comparable, and often much larger, than the number of subjects in the study. and (2) the covariate space is highly structured, and in some cases it is desirable to incorporate this structural information in to the model building proces...
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作者：Li, Lexin; Li, Bing; Zhu, Li-Xing
作者单位：North Carolina State University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Hong Kong Baptist University
摘要：In many regression applications, the predictors fall naturally into a number of groups or domains, and it is often desirable to establish a domain-specific relation between the predictors and the response. In this article, we consider dimension reduction that incorporates such domain knowledge. The proposed method is based on the derivative of the conditional mean, where the differential operator is constrained to the form of a direct sum. This formulation also accommodates the situations wher...
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作者：Freyermuth, Jean-Marc; Ombao, Hernando; von Sachs, Rainer
作者单位：Universite Catholique Louvain; Brown University
摘要：This article develops a method for estimating the spectrum of a stationary process using time series traces recorded from experimental designs. Our procedure estimates the common log-spectrum and the variability over the traces (or subjects) using a mixed effects model. We combine spatially adaptive smoothing methods with recursive dyadic partitioning to construct a model for predicting subject-specific effects. The method is easy to implement and can handle large datasets because it uses the ...
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作者：Paparoditis, Efstathios
作者单位：University of Cyprus
摘要：We propose a simple and powerful procedure to validate the assumption of weak stationarity in time series analysis. Our focus is on processes with a slowly varying autocovariance structure. The procedure evaluates the supremum over time of the L-2-distance between the local sample spectral density (local periodogram) calculated using a segment of observations falling within a rolling window and an estimator of the spectral density obtained using the entire time series at hand. Large sample pro...
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作者：Ren, Lu; Dunson, David; Lindroth, Scott; Carin, Lawrence
作者单位：Duke University; Duke University; Duke University
摘要：The dynamic hierarchical Dirichlet process (dHDP) is developed to model complex sequential data, with a focus on audio signals from music. The music is represented in terms of a sequence of discrete observations, and the sequence is modeled using a hidden Markov model (HMM) with time-evolving parameters. The dHDP imposes the belief that observations that are temporally proximate are more likely to be drawn from HMMs with similar parameters, while also allowing for innovation associated with ab...
