-
作者：Rue, H
作者单位：Norwegian University of Science & Technology (NTNU)
摘要：This paper demonstrates how Gaussian Markov random fields (conditional autoregressions) can be sampled quickly by using numerical techniques for sparse matrices. The algorithm is general and efficient, and expands easily to various forms for conditional simulation and evaluation of normalization constants. We demonstrate its use by constructing efficient block updates in Markov chain Monte Carlo algorithms for disease mapping.
-
作者：Xie, SX; Wang, CY; Prentice, RL
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health; Fred Hutchinson Cancer Center
摘要：Regression parameter estimation in the Cox failure time model is considered when regression variables are subject to measurement error, Assuming that repeat regression vector measurements adhere to a classical measurement model, we can consider an ordinary regression calibration approach in which the unobserved covariates are replaced by an estimate of their conditional expectation given available covariate measurements. However, since the rate of withdrawal from the risk set across the time a...
-
作者：DiRienzo, AG; Lagakos, SW
作者单位：Harvard University; Harvard T.H. Chan School of Public Health
摘要：We examine the asymptotic and small sample properties of model-based and robust tests of the null hypothesis of no randomized treatment affect based on the partial likelihood arising from an arbitrarily misspecified Cox proportional hazards model. When the distribution of the censoring variable is either conditionally independent of the treatment group given covariates or conditionally independent of covariates given the treatment group, the numerators of the partial likelihood treatment score...
-
作者：Kennedy, MC; O'Hagan, A
作者单位：University of Sheffield
摘要：We consider prediction and uncertainty analysis for systems which are approximated using complex mathematical models. Such models, implemented as computer codes, are often generic in the sense that by a suitable choice of some of the model's input parameters the code can be used to predict the behaviour of the system in a variety of specific applications. However, in any specific application the values of necessary parameters may be unknown. In this case, physical observations of the system in...
-
作者：Stroud, JR; Müller, P; Sansó, B
作者单位：University of Chicago; Duke University; Simon Bolivar University
摘要：We propose a model for non-stationary spatiotemporal data. To account for spatial variability, we model the mean function at each time period as a locally weighted mixture of linear regressions. To incorporate temporal variation, we allow the regression coefficients to change through time, The model is cast In a Gaussian state space framework, which allows us to include temporal components such as trends, seasonal effects and autoregressions, and permits a fast implementation and full probabil...
-
作者：Garthwaite, PH; Al-Awadhi, SA
作者单位：Open University - UK; Kuwait University
摘要：Elicitation methods are proposed for quantifying expert opinion about a multivariate normal sampling model. The natural conjugate prior family imposes a relationship between the mean vector and the covariance matrix that can portray an expert's opinion poorly. Instead we assume that opinions about the mean and the covariance are independent and suggest innovative forms of question which enable the expert to quantify separately his or her opinion about each of these parameters. Prior opinion ab...
-
作者：Lewis, SM; Dean, AM
作者单位：University of Southampton; University System of Ohio; Ohio State University
摘要：One of the main advantages of factorial experiments is the information that they can offer on interactions. When there are many factors to be studied, some or all of this information is often sacrificed to keep the size of an experiment economically feasible. Two strategies for group screening are presented for a large number of factors, over two stages of experimentation, with particular emphasis on the detection of interactions. One approach estimates only main effects at the first stage (cl...
-
作者：Barndorff-Nielsen, OE; Shephard, N
作者单位：University of Oxford; Aarhus University
摘要：Non-Gaussian processes of Ornstein-Uhlenbeck (OU) type offer the possibility of capturing important distributional deviations from Gaussianity and for flexible modelling of dependence structures. This paper develops this potential, drawing on and extending powerful results from probability theory for applications in statistical analysis. Their power is illustrated by a sustained application of OU processes within the context of finance and econometrics. We construct continuous time stochastic ...
-
作者：Bogacka, B; Wynn, H; Cox, DR; Garratt, M; Bailey, RA; Gilmour, SG; Curnow, RN; Longford, NT; Laycock, PJ; Atkinson, A; Torsney, B; Mee, R; Ankenman, BE; Disney, J; Mukerjee, R; Pan, GH; Wu, CFJ
作者单位：University of London
-
作者：Bura, E; Cook, RD
作者单位：George Washington University; University of Minnesota System; University of Minnesota Twin Cities
摘要：A new estimation method for the dimension of a regression at the outset of an analysis is proposed. A linear subspace spanned by projections of the regressor vector X, which contains part or all of the modelling information for the regression of a vector Y on X, and its dimension are estimated via the means of parametric inverse regression. Smooth parametric curves are fitted to the p inverse regressions via a multivariate linear model. No restrictions are placed on the distribution of the reg...
