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作者：Zhang, Ying
作者单位：University of Iowa
摘要：We study the nonparametric k-sample test problem with panel count data. The asymptotic normality of a smooth functional of the nonparametric maximum pseudo-likelihood estimator (Wellner & Zhang, 2000) is established under some mild conditions. We construct a class of easy-to-implement nonparametric tests for comparing mean functions of k populations based on this asymptotic normality. We conduct various simulations to validate and compare the tests. The simulations show that the tests perform ...
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作者：Chen, Ming-Hui; Ibrahim, Joseph G.; Shao, Qi-Man
作者单位：University of Connecticut; University of North Carolina; University of North Carolina Chapel Hill; Hong Kong University of Science & Technology
摘要：In this paper, we carry out an in-depth theoretical investigation of Bayesian inference for the Cox regression model. We establish necessary and sufficient conditions for posterior propriety of the regression coefficient, beta, in Cox's partial likelihood, which can be obtained as the limiting marginal posterior distribution of beta through the specification of a gamma process prior for the cumulative baseline hazard and a uniform improper prior for beta. We also examine necessary and sufficie...
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作者：Wang, Xinlei; Lim, Johan; Stokes, S. Lynne
作者单位：Southern Methodist University; Yonsei University; Southern Methodist University
摘要：For the problem of dual system estimation, we propose a Bayesian treed capture-recapture model to account for heterogeneity of capture probabilities where individual auxiliary information is available. The model uses a binary tree to partition the covariate space into 'homogeneous' regions, within each of which the capture response can be described adequately by a simple model that assumes equal catchability. The attractive features of the proposed model include reduction of correlation bias, ...
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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：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：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...
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作者：Ye, Huajun; Pan, Jianxin
作者单位：University of Manchester
摘要：When used for modelling longitudinal data generalised estimating equations specify a working structure for the within-subject covariance matrices, aiming to produce efficient parameter estimators. However, misspecification of the working covariance structure may lead to a large loss of efficiency of the estimators of the mean parameters. In this paper we propose an approach for joint modelling of the mean and covariance structures of longitudinal data within the framework of generalised estima...
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作者：Chen, Shu-Chuan; Lindsay, Bruce G.
作者单位：Arizona State University; Arizona State University-Tempe; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：We develop a new method for building a hierarchical tree from binary sequence data. It is based on an ancestral mixture model. The sieve parameter in the model plays the role of time in the evolutionary tree of the sequences. By varying the sieve parameter, one can create a hierarchical tree that estimates the population structure at each fixed backward point in time. Application to the clustering of the mitochondrial DNA sequences of Griffiths & Tavare (1994) shows that the approach performs ...
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作者：Nan, Bin; Yu, Menggang; Kalbfleisch, John D.
作者单位：University of Michigan System; University of Michigan; Indiana University System; Indiana University Indianapolis; University of Michigan System; University of Michigan
摘要：Right-censored data from a classical case-cohort design and a stratified case-cohort design are considered. In the classical case-cohort design the subcohort is obtained as a simple random sample of the entire cohort, whereas in the stratified design this subcohort is elected by independent Bernoulli sampling with arbitrary selection probabilities. For each design and under a linear regression model, methods for estimating the regression parameters are proposed and analysed. These methods are ...
