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作者：Chen, MH; Dey, DK; Ibrahim, JG
作者单位：University of Connecticut; University of North Carolina; University of North Carolina Chapel Hill
摘要：We propose a general Bayesian criterion for model assessment for categorical data called the weighted L measure, which is constructed from the posterior predictive distribution of the data. The measure is based on weighting the observations according to the sampling variance of their future response vector. The weight component in the weighted L measure plays the role of a penalty term in the criterion, in which a greater weight assigned to covariate values implies a greater penalty term on th...
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作者：Félix-Medina, MH; Thompson, SK
作者单位：Universidad Autonoma de Sinaloa; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：We present a multi-phase variant of adaptive cluster sampling which allows the sampler to control the number of measurements of the variable of interest. A first-phase sample is selected using an adaptive cluster sampling design based on an inexpensive auxiliary variable associated with the survey variable. Then the network structure of the adaptive cluster sample is used to select an ordinary one-phase or two-phase subsample of units and the values of the survey variable associated with those...
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作者：Olhede, SC; Walden, AT
作者单位：Imperial College London
摘要：We introduce so-called analytic stationary wavelet transform thresholding where, using the discrete Hilbert transform, we create a complex-valued 'analytic' vector from which an amplitude vector is defined. Thresholding of a real-valued wavelet coefficient at some transform level is carried out according to the corresponding value in this amplitude vector; relevant statistical results follow from properties of the discrete Hilbert transform. Analytic stationary wavelet transform thresholding i...
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作者：Drton, M; Perlman, MD
作者单位：University of Washington; University of Washington Seattle
摘要：A multivariate Gaussian graphical Markov model for an undirected graph G, also called a covariance selection model or concentration graph model, is defined in terms of the Markov properties, i.e. conditional independences associated with G, which in turn are equivalent to specified zeros among the set of pairwise partial correlation coefficients. By means of Fisher's z-transformation and Sidak's correlation inequality, conservative simultaneous confidence intervals for the entire set of partia...
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作者：Olhede, SC; McCoy, EJ; Stephens, DA
作者单位：Imperial College London
摘要：Seasonally persistent models were first introduced by Andel (1986) and Gray et al. (1989) to extend autoregressive moving-average and fractionally differenced models and to encompass long-memory quasi-periodic behaviour. These models are, for certain ranges of parameters, stationary, and we prove here that the behaviour of the periodogram and other tapered estimators cannot be simply extended from the work of Kunsch (1986) and Hurvich & Beltrao (1993) on long memory induced by a pole at the or...
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作者：Fuh, CD; Hu, I
作者单位：Academia Sinica - Taiwan; Hong Kong University of Science & Technology
摘要：We propose a method for finding the alternative distribution in importance sampling. The alternative distribution is optimal in the sense that the asymptotic variance is minimised for estimating tail probabilities of asymptotically normal statistics. Our contribution to importance sampling is three-fold. To begin with, we obtain an explicit expression for the mean of the optimal alternative distribution and the expression motivates a recursive approximation algorithm. Secondly, a new multi-dim...
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作者：Qu, A; Song, PXK
作者单位：Oregon State University; York University - Canada
摘要：In the presence of data contamination or outliers, some empirical studies have indicated that the two methods of generalised estimating equations and quadratic inference functions appear to have rather different robustness behaviour. This paper presents a theoretical investigation from the perspective of the influence function to identify the causes for the difference. We show that quadratic inference functions lead to bounded influence functions and the corresponding M-estimator has a redesce...
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作者：Ghosh, M; Maiti, T
作者单位：State University System of Florida; University of Florida; Iowa State University
摘要：We propose pseudo empirical best linear unbiased estimators of small-area means based on natural exponential family quadratic variance function models when the basic data consist of survey-weighted estimators of these means, area-specific covariates and certain summary measures involving the weights. We also provide explicit approximate mean squared errors of these estimators in the spirit of Prasad & Rao (1990), and these estimators can be readily evaluated. A simulation study is undertaken t...
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作者：Craiu, RV; Duchesne, T
作者单位：University of Toronto; Laval University
摘要：In this paper we propose inference methods based on the Em algorithm for estimating the parameters of a weakly parameterised competing risks model with masked causes of failure and second-stage data. With a carefully chosen definition of complete data, the maximum likelihood estimation of the cause-specific hazard functions and of the masking probabilities is performed via an Em algorithm. Both the E- and m-steps can be solved in closed form under the full model and under some restricted model...
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作者：Dette, H; Kwiecien, R
作者单位：Ruhr University Bochum; RWTH Aachen University
摘要：Classical regression analysis is usually performed in two steps. In a first step an appropriate model is identified to describe the data-generating process and in a second step statistical inference is performed in the identified model. In this paper we investigate a sequential and a non-sequential design strategy, which take into account these different goals of the analysis for a class of nested models. It is demonstrated that non-sequential designs usually identify the 'correct' model with ...
