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作者：Brown, PJ; Vannucci, M; Fearn, T
作者单位：University of Kent; Texas A&M University System; Texas A&M University College Station; University of London; University College London
摘要：When a number of distinct models contend for use in prediction, the choice of a single model can offer rather unstable predictions. In regression, stochastic search variable selection with Bayesian model averaging offers a cure for this robustness issue but at the expense of requiring very many predictors. Here we look at Bayes model averaging incorporating variable selection for prediction. This offers similar mean-square errors of prediction but with a vastly reduced predictor space. This ca...
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作者：Fernández, C; Green, PJ
作者单位：Lancaster University; University of Bristol
摘要：The paper develops mixture models for spatially indexed data. We confine attention to the case of finite, typically irregular, patterns of points or regions with prescribed spatial relationships, and to problems where it is only the weights in the mixture that vary from one location to another. Our specific focus is on Poisson-distributed data, and applications in disease mapping. We work in a Bayesian framework, with the Poisson parameters drawn from gamma priors, and an unknown number of com...
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作者：Xia, YC; Tong, H; Li, WK; Zhu, LX
作者单位：University of Cambridge; University of Jinan; University of Hong Kong; University of London; London School Economics & Political Science; Chinese Academy of Sciences
摘要：Searching for an effective dimension reduction space is an important problem in regression, especially for high dimensional data. We propose an adaptive approach based on semiparametric models, which we call the (conditional) minimum average variance estimation (MAVE) method, within quite a general setting. The MAVE method has the following advantages. Most existing methods must undersmooth the nonparametric link function estimator to achieve a faster rate of consistency for the estimator of t...
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作者：Hall, P; Humphreys, K; Titterington, DM
作者单位：University of Glasgow; Australian National University; Karolinska Institutet
摘要：Variational methods have been proposed for obtaining deterministic lower bounds for log-likelihoods within missing data problems, but with little formal justification or investigation of the worth of the lower bound surfaces as tools for inference. We provide, within a general Markovian context, sufficient conditions under which estimators from the variational approximations are asymptotically equivalent to maximum likelihood estimators, and we show empirically, for the simple example of a fir...
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作者：Spiegelhalter, DJ; Best, NG; Carlin, BR; van der Linde, A
作者单位：University of Cambridge; MRC Biostatistics Unit; Imperial College London; University of Minnesota System; University of Minnesota Twin Cities; University of Bremen
摘要：We consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly defined. Using an information theoretic argument we derive a measure P-D for the effective number of parameters in a model as the difference between the posterior mean of the deviance and the deviance at the posterior means of the parameters of interest. In general P-D approximately corresponds to the trace of the product of Fisher's information and the posterior covariance, which ...
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作者：Barndorff-Nielsen, OE; Shephard, N
作者单位：University of Oxford; Aarhus University
摘要：The availability of intraday data on the prices of speculative assets means that we can use quadratic variation-like measures of activity in financial markets, called realized volatility, to study the stochastic properties of returns. Here, under the assumption of a rather general stochastic volatility model, we derive the moments and the asymptotic distribution of the realized volatility error-the difference between realized volatility and the discretized integrated volatility (which we call ...
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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.
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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...
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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...
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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...
