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作者：He, XM; Zhu, ZY; Fung, WK
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; East China Normal University; University of Hong Kong
摘要：This paper considers an extension of M-estimators in semiparametric models for independent observations to the case of longitudinal data. We approximate the nonparametric function by a regression spline, and any M-estimation algorithm for the usual linear models can then be used to obtain consistent estimators of the model and valid large-sample inferences about the regression parameters without any specification of the error distribution and the covariance structure. Included as special cases...
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作者：Fu, B; Li, WK; Fung, WK
作者单位：University of Hong Kong
摘要：We give several definitions of residual autocorrelations and derive their joint asymptotic distribution for the panel time series model of Hjellvik & Tjostheim (1999a). A portmanteau goodness-of-fit test arises naturally from the asymptotic distribution. Simulation results show that the asymptotic standard errors compared satisfactorily with the empirical standard errors, that the goodness-of-fit test has reasonable empirical size, and that it is powerful enough to be useful with a modest samp...
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作者：Daniels, MJ; Pourahmadi, M
作者单位：Iowa State University; Northern Illinois University
摘要：Parsimonious modelling of the within-subject covariance structure while heeding its positive-definiteness is of great importance in the analysis of longitudinal data. Using the Cholesky decomposition and the ensuing unconstrained and statistically meaningful reparameterisation, we provide a convenient and intuitive framework for developing conditionally conjugate prior distributions for covariance matrices and show their connections with generalised inverse Wishart priors. Our priors offer man...
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作者：Downs, TD; Mardia, KV
作者单位：University of Leeds
摘要：A new model for an angular regression link function is introduced. The model employs an angular scale parameter, incorporates proper and improper rotations as special cases, and is equivalent to the Mobius circle mapping for complex variables. Desirable properties of the circle mapping carry over to angular regression. Parameter estimation and inferential methods are developed and illustrated.
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作者：Biswas, A; Chaudhuri, P
作者单位：Indian Statistical Institute; Indian Statistical Institute Kolkata; Indian Statistical Institute; Indian Statistical Institute Kolkata
摘要：We consider experimental designs in a regression set-up where the unknown regression function belongs to a known family of nested linear models. The objective of our design is to select the correct model from the family of nested models as well as to estimate efficiently the parameters associated with that model. We show that our proposed design is able to choose the true model with probability tending to one as the number of trials grows to infinity. We also establish that our selected design...
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作者：Scharfstein, DO; Robins, JM
作者单位：Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health
摘要：We present a method for estimating the survival curve of a continuous failure time random variable from right-censored data. Our method allows adjustment for informative censoring due to measured prognostic factors for time-to-event and censoring while simultaneously quantifying the sensitivity of the inference to residual dependence between failure and censoring due to unmeasured factors. We present the results of a simulation study and illustrate our approach using data from the AIDS Clinica...
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作者：Pérez, JM; Berger, JO
作者单位：Simon Bolivar University; Duke University
摘要：We consider the problem of comparing parametric models using a Bayesian approach. A new method of developing prior distributions for the model parameters is presented, called the expected-posterior prior approach. The idea is to define the priors for all models from a common underlying predictive distribution, in such a way that the resulting priors are amenable to modern Markov chain Monte Carlo computational techniques, The approach has subjective Bayesian and default Bayesian implementation...
