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作者：Chopin, N.; Jacob, P. E.; Papaspiliopoulos, O.
作者单位：Institut Polytechnique de Paris; ENSAE Paris; Institut Polytechnique de Paris; ENSAE Paris; Universite PSL; Universite Paris-Dauphine; ICREA; Pompeu Fabra University
摘要：. We consider the generic problem of performing sequential Bayesian inference in a state space model with observation process y, state process x and fixed parameter . An idealized approach would be to apply the iterated batch importance sampling algorithm of Chopin. This is a sequential Monte Carlo algorithm in the -dimension, that samples values of , reweights iteratively these values by using the likelihood increments and rejuvenates the -particles through a resampling step and a Markov chai...
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作者：Lee, Youngjo; Bjornstad, Jan F.
作者单位：Seoul National University (SNU); Statistics Norway
摘要：To date, only frequentist, Bayesian and empirical Bayes approaches have been studied for the large-scale inference problem of testing simultaneously hundreds or thousands of hypotheses. Their derivations start with some summarizing statistics without modelling the basic responses. As a consequence testing procedures have been developed without necessarily checking model assumptions, and empirical null distributions are needed to avoid the problem of rejecting all null hypotheses when the sampl...
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作者：Rukhin, Andrew L.
作者单位：National Institute of Standards & Technology (NIST) - USA
摘要：. Several new estimators of the between-study variability in a heterogeneous random effects meta-analysis model are derived. One is the unbiased statistic which is locally optimal for small values of the parameter. Others are Bayes procedures within a class of quadratic statistics for a diffuse prior with different choices of the prior mean. These estimators are compared with the DerSimonianLaird procedure and the Hedges statistic in particular via the quadratic risk of the treatment effect es...
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作者：Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
作者单位：Korea University; Seoul National University (SNU); Stanford University
摘要：Estimation of high dimensional covariance matrices is known to be a difficult problem, has many applications and is of current interest to the larger statistics community. In many applications including the so-called large p, small n' setting, the estimate of the covariance matrix is required to be not only invertible but also well conditioned. Although many regularization schemes attempt to do this, none of them address the ill conditioning problem directly. We propose a maximum likelihood ap...
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作者：Xiao, Luo; Li, Yingxing; Ruppert, David
作者单位：Johns Hopkins University; Xiamen University; Cornell University
摘要：We propose a fast penalized spline method for bivariate smoothing. Univariate P-spline smoothers are applied simultaneously along both co-ordinates. The new smoother has a sandwich form which suggested the name sandwich smoother' to a referee. The sandwich smoother has a tensor product structure that simplifies an asymptotic analysis and it can be fast computed. We derive a local central limit theorem for the sandwich smoother, with simple expressions for the asymptotic bias and variance, by s...
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作者：Griffin, J. E.; Kolossiatis, M.; Steel, M. F. J.
作者单位：University of Kent; Cyprus University of Technology; University of Warwick
摘要：A methodology for the simultaneous Bayesian non-parametric modelling of several distributions is developed. Our approach uses normalized random measures with independent increments and builds dependence through the superposition of shared processes. The properties of the prior are described and the modelling possibilities of this framework are explored in detail. Efficient slice sampling methods are developed for inference. Various posterior summaries are introduced which allow better understa...
