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作者：Newton, MA; Zhang, YL
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：The mixture of Dirichlet processes posterior that arises in nonparametric Bayesian analysis has been analysed most effectively using Markov chain Monte Carlo. As a computationally simple alternative, we introduce a recursive approximation based on one-step posterior predictive distributions. Asymptotic calculations provide theoretical support for this approximation, and we investigate its actual behaviour in several numerical examples. From a non-Bayesian perspective, this new recursion may be...
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作者：Cavanaugh, JE; Johnson, WO
作者单位：University of Missouri System; University of Missouri Columbia; University of California System; University of California Davis
摘要：An important inferential objective in state space modelling is to recover unobserved states using fixed-interval smoothing. Thus, the identification of cases which have a substantial influence on the smoothers is a relevant practical problem. To facilitate this identification, we propose a case-deletion diagnostic which can be easily computed using the outputs of the standard filtering and smoothing algorithms. Our diagnostic is defined as the Kullback-Leibler directed divergence between two v...
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作者：Lee, SMS; Young, GA
作者单位：University of Hong Kong; University of Cambridge
摘要：We consider construction of two-sided nonparametric confidence intervals in a smooth function model setting. A nonparametric likelihood approach based on Stein's least favourable family is proposed as an alternative to empirical likelihood. The approach enjoys the same asymptotic:properties as empirical likelihood, but is analytically and computationally less cumbersome. The simplicity of the method allows us to propose and analyse asymptotic and bootstrapping techniques as a means of reducing...
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作者：Gu, MG; Follmann, D; Geller, NL
作者单位：Chinese University of Hong Kong; National Institutes of Health (NIH) - USA; NIH National Heart Lung & Blood Institute (NHLBI)
摘要：This paper considers a general class of statistics for testing the equality of two survival distributions in clinical trials with sequential monitoring. The tests can be expressed as Lebesgue-Stieltjes integrals of a weight function with respect to the difference between two survival distributions. Prominent members of this class include the two-sample difference in Kaplan-Meier estimates, the test of medians (Brookmeyer & Crowley, 1982), a truncated version of Efron's (1967) test and the Pepe...
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作者：Jorgensen, B; Lundbye-Christensen, S; Song, PXK; Sun, L
作者单位：University of Southern Denmark; Aalborg University; York University - Canada; University of British Columbia
摘要：We propose a nonstationary state space model for multivariate longitudinal count data driven by a latent gamma Markov process. The Poisson counts are assumed to be conditionally independent given the latent process, both over time and across categories. We consider a regression model where time-varying covariates may enter via either the Poisson model or the latent gamma process. Estimation is based on the Kalman smoother, and we consider analysis of residuals from both the Poisson model and t...
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作者：Slate, EH
作者单位：Cornell University
摘要：This paper proposes diagnostics that can indicate regions where multivariate distributions are poorly behaved in the sense that they are far from normal. The measure of nonnormality developed by Slate (1994) for univariate distributions is extended to multivariate parametric models by application to univariate marginal and conditional distributions. The approach is illustrated for univariate conditional distributions using dynamic graphics in Xlisp-Stat (Tierney, 1990). Examples show that the ...
