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作者：Ghosal, S; Ghosh, JK; Ramamoorthi, RV
作者单位：Vrije Universiteit Amsterdam; Indian Statistical Institute; Indian Statistical Institute Kolkata; Michigan State University; Purdue University System; Purdue University
摘要：A Dirichlet mixture of normal densities is a useful choice for a prior distribution on densities in the problem of Bayesian density estimation. In the recent years, efficient Markov chain Monte Carlo method for the computation of the posterior distribution has been developed. The method has been applied to data arising from different fields of interest. The important issue of consistency was however left open. In this paper, we settle this issue in affirmative.
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作者：Jiang, JM
作者单位：University System of Ohio; Case Western Reserve University
摘要：We propose a method of inference for generalized linear mixed models (GLMM) that in many ways resembles the method of least squares. We also show that adequate inference about GLMM can be made based on the conditional likelihood on a subset of the random effects. One of the important features of our methods is that they rely on weak distributional assumptions about the random effects. The methods proposed are also computationally feasible. Asymptotic behavior of the estimates is investigated. ...
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作者：Hallin, M; Jurecková, J
作者单位：Universite Libre de Bruxelles; Charles University Prague
摘要：Locally asymptotically optimal tests based on autoregression rank scores are constructed for testing Linear constraints on the structural parameters of AR processes. Such tests are asymptotically distribution free and do not require the estimation of nuisance parameters. They constitute robust, flexible and quite powerful alternatives to existing methods such as the classical correlogram-based parametric tests, the Gaussian Lagrange multiplier tests, the optimal non-Gaussian and ranked residua...
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作者：Streitberg, B
作者单位：University of Hamburg
摘要：Based on a revised Lancaster-type representation of the additive interactions associated with a probability measure, a new approach for the analysis of high-dimensional contingency tables is proposed. The approach is essentially model-free because the additive interaction tensor is merely a convenient reparameterization of the given table. Single interaction terms are investigated using the bootstrap method whose first-order asymptotic validity is immediate. The global structure can be investi...
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作者：Babu, GJ; Pathak, PK; Rao, CR
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Michigan State University
摘要：Rao, Pathak and Koltchinskii have recently studied a sequential approach to resampling in which resampling is carried out sequentially one-by-one (with replacement each time) until the bootstrap sample contains m approximate to (1 - e(-1))n approximate to 0.632n distinct observations from the original sample. In our previous work, we have established that the main empirical characteristics of the sequential bootstrap go through, in the sense of being within a distance O(n(-3/4)) from those of ...
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作者：Lee, S; Wei, CZ
作者单位：Seoul National University (SNU); Academia Sinica - Taiwan
摘要：Motivated by Gaussian tests for a time series, we are led to investigate the asymptotic behavior of the residual empirical processes of stochastic regression models. These models cover the fixed design regression models as well as general AR(q) models. Since the number of the regression coefficients is allowed to grow as the sample size increases, the obtained results are also applicable to nonlinear regression and stationary AR(infinity) models. In this paper, we first derive an oscillation-l...
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作者：Cesa-Bianchi, N; Lugosi, G
作者单位：University of Milan; Pompeu Fabra University
摘要：Sequential randomized prediction of an arbitrary binary sequence is investigated. No assumption is made on the mechanism of generating the bit sequence. The goal of the predictor is to minimize its relative loss (or regret), that; is, to make almost as few mistakes as the best expert in a fixed, possibly infinite, set of experts. We point out a surprising connection between this prediction problem and empirical process theory. First, in the special case of static (memoryless) expert, we comple...
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作者：de Haan, L; Sinha, AK
作者单位：Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University Rotterdam
摘要：Let (X-1, Y-1), (X-2, Y-2),..., (X-n, Y-n) be a random sample from a bivariate distribution function F which is in the domain of attraction of a bivariate extreme value distribution function G. A subset C of R-2 is given, which contains none of the observations. We shall give an asymptotic confidence interval for Pr((X-i, Y-i) is an element of C) under certain conditions.
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作者：Geskus, R; Groeneboom, P
作者单位：Delft University of Technology
摘要：For a version of the interval censoring model, case 2, in which the observation intervals are allowed to be arbitrarily small, we consider estimation of functionals that are differentiable along Hellinger differentiable paths. The asymptotic information lower bound for such functionals can be represented as the squared L-2-norm of the canonical gradient in the observation space. This canonical gradient has an implicit expression as a solution of an integral equation that does not belong to one...
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作者：Bingham, DR; Sitter, RR
作者单位：Simon Fraser University
摘要：Fractional factorial (FF) designs are commonly used in industrial experiments to identify factors affecting a process. When it is expensive or difficult to change the levels of some of the factors, fractional factorial split-plot (FFSP) designs represent a practical design option. Though FFSP design matrices correspond to FF design matrices, the randomization structure of the FFSP design is different. In this paper we discuss the impact of randomization restrictions on the choice of FFSP desig...
