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作者：Madsen, J
作者单位：University of Copenhagen
摘要：An extension of the class of GS-LCI normal models introduced by Andersson and Madsen is defined and studied. The models are defined in terms of symmetry restrictions given by a finite group and conditional independence restrictions given by an acyclic directed graph. Maximum likelihood estimation of the parameters in the models is discussed.
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作者：Gilbert, PB
作者单位：Harvard University; Harvard T.H. Chan School of Public Health
摘要：Vardi [Ann. Statist. 13 178-203 (1985)] introduced an s-sample biased sampling model with known selection weight functions, gave a condition under which the common underlying probability distribution G is uniquely estimable and developed simple procedure for computing the nonparametric maximum likelihood estimator (NPMLE) G(n) of G. Gill, Vardi and Wellner thoroughly described the large sample properties of Vardi's NPMLE, giving results on uniform consistency, convergence of root n (G(n) - G) ...
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作者：Frigessi, A; Gåsemyr, J; Rue, H
作者单位：University of Oslo; Norwegian University of Science & Technology (NTNU)
摘要：Two coupled Gibbs sampler chains, both with invariant probability density pi, are run in parallel so that the chains are negatively correlated. We define an asymptotically unbiased estimator of the pi -expectation E( f(X)) which achieves significant variance reduction with respect to the usual Gibbs sampler at comparable computational cost. The variance of the estimator based on the new algorithm is always smaller than the variance of a single Gibbs sampler chain, if pi is attractive and f is ...
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作者：Peskir, G; Shiryaev, AN
作者单位：Aarhus University; University of Zagreb; Russian Academy of Sciences; Steklov Mathematical Institute of the Russian Academy of Sciences
摘要：We present the explicit solution of the Bayesian problem of sequential testing of two simple hypotheses about the intensity of an observed Poisson process. The method of proof consists of reducing the initial problem to a free-boundary differential-difference Stephan problem and solving the latter by use of the principles of smooth and continuous fit. A rigorous proof of the optimality of the Wald's sequential probability ratio test in the variational formulation of the problem is obtained as ...
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作者：Skouras, K
作者单位：University of London; University College London
摘要：The class of nonlinear stochastic regression models includes most of the linear and nonlinear models used in time series, stochastic control and stochastic approximation schemes. The consistency of least squares estimators was established first by Lai. We present another set of sufficient conditions for consistency, which avoid the use of partial derivatives and are closer in spirit to the conditions presented by Wu for non-stochastic regression models with independent errors.
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作者：Ghosal, S; Ghosh, JK; Van der Vaart, AW
作者单位：Vrije Universiteit Amsterdam; Indian Statistical Institute; Indian Statistical Institute Kolkata
摘要：We consider the asymptotic behavior of posterior distributions and Bayes estimators for infinite-dimensional statistical models. We give general results on the rate of convergence of the posterior measure. These are applied to several examples, including priors on finite sieves, log-spline models, Dirichlet processes and interval censoring.
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作者：Datta, GS; Mukerjee, R; Ghosh, M; Sweeting, TJ
作者单位：University System of Georgia; University of Georgia; State University System of Florida; University of Florida; Indian Institute of Management (IIM System); Indian Institute of Management Calcutta; University of Surrey
摘要：We characterize priors which asymptotically match the posterior coverage probability of a Bayesian prediction region with the corresponding frequentist coverage probability. This is done considering both posterior quantiles and highest predictive density regions with reference to a future observation. The resulting priors are shown to be invariant under reparameterization. The role of Jeffreys' prior in this regard is also investigated. It is further shown that, for any given prior, it may be ...
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作者：Csiszár, I; Shields, PC
作者单位：HUN-REN; HUN-REN Alfred Renyi Institute of Mathematics; Hungarian Academy of Sciences; University System of Ohio; University of Toledo
摘要：The Bayesian Information Criterion (BIC) estimates the order of a Markov chain (with finite alphabet A) from observation of a sample path x(1), x(2), ..., x(n), as that value k = (k) over cap that minimizes the sum of the negative logarithm of the kth order maximum likelihood and the penalty term \A\(k)(\A\-1)/2. We show that (k) over cap equals the correct order of the chain, eventually almost surely as it --> infinity, thereby strengthening earlier consistency results that assumed an apriori...
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作者：Dette, H; Franke, T
作者单位：Ruhr University Bochum
摘要：In the common polynomial regression model of degree m we consider the problem of determining the D- and D-1-optimal designs subject to certain constraints for the D-1-efficiencies in the models of degree m - j, m - j + 1..... m + k(m > j greater than or equal to 0, k greater than or equal to 0 given). We present a complete solution of these problems, which on the one hand allow a fast computation of the constrained optimal designs and on the other hand give an answer to the question of the exi...
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作者：Eggermont, PPB; LaRiccia, VN
作者单位：University of Delaware
摘要：We study the nonparametric estimation of univariate monotone and unimodal densities using the maximum smoothed likelihood approach. The monotone estimator is the derivative of the least concave majorant of the distribution corresponding to a kernel estimator. We prove that the mapping on distributions Phi with density phi, phi bar right arrow the derivative of the least concave majorant of Phi, is a contraction in all L-P norms (1 less than or equal to p less than or equal to infinity), and so...
