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作者：Qian, Peter Z. G.; Wu, C. F. Jeff
作者单位：University of Wisconsin System; University of Wisconsin Madison; University System of Georgia; Georgia Institute of Technology
摘要：We propose an approach to constructing a new type of design, a sliced space-filling design, intended for computer experiments with qualitative and quantitative factors. The approach starts with constructing a Latin hypercube design based on a special orthogonal array for the quantitative factors and then partitions the design into groups corresponding to different level combinations of the qualitative factors. The points in each group have good space-filling properties. Some illustrative examp...
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作者：Qian, Peter Z. G.
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：We propose an approach to constructing nested Latin hypercube designs. Such designs are useful for conducting multiple computer experiments with different levels of accuracy. A nested Latin hypercube design with two layers is defined to be a special Latin hypercube design that contains a smaller Latin hypercube design as a subset. Our method is easy to implement and can accommodate any number of factors. We also extend this method to construct nested Latin hypercube designs with more than two ...
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作者：Kim, Jae Kwang; Rao, J. N. K.
作者单位：Iowa State University; Carleton University
摘要：Variance estimation after imputation is an important practical problem in survey sampling. When deterministic imputation or stochastic imputation is used, we show that the variance of the imputed estimator can be consistently estimated by a unifying linearize and reverse approach. We provide some applications of the approach to regression imputation, fractional categorical imputation, multiple imputation and composite imputation. Results from a simulation study, under a factorial structure for...
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作者：Kosmidis, Ioannis; Firth, David
作者单位：University of Warwick
摘要：In Firth (1993, Biometrika) it was shown how the leading term in the asymptotic bias of the maximum likelihood estimator is removed by adjusting the score vector, and that in canonical-link generalized linear models the method is equivalent to maximizing a penalized likelihood that is easily implemented via iterative adjustment of the data. Here a more general family of bias-reducing adjustments is developed for a broad class of univariate and multivariate generalized nonlinear models. The res...
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作者：Hannig, Jan; Lee, Thomas C. M.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; Chinese University of Hong Kong
摘要：We apply Fisher's fiducial idea to wavelet regression, first developing a general methodology for handling model selection problems within the fiducial framework. We propose fiducial-based methods for wavelet curve estimation and the construction of pointwise confidence intervals. We show that these confidence intervals have asymptotically correct coverage. Simulations demonstrate that they possess promising empirical properties.
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作者：Sun, Fasheng; Liu, Min-Qian; Lin, Dennis K. J.
作者单位：Nankai University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Latin hypercube designs have found wide application. Such designs guarantee uniform samples for the marginal distribution of each input variable. We propose a method for constructing orthogonal Latin hypercube designs in which all the linear terms are orthogonal not only to each other, but also to the quadratic terms. This construction method is convenient and flexible, and the resulting designs can accommodate many more factors than can existing ones.
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作者：Luo, Xiaodong; Tsai, Wei Yann
作者单位：Icahn School of Medicine at Mount Sinai; Columbia University
摘要：To estimate the lifetime distribution of right-censored length-biased data, we propose a pseudo-partial likelihood approach that allows us to derive two nonparametric estimators. With its closed-form estimators and explicit limiting variances, this approach retains the simplicity of conditional analysis, and has only a small efficiency loss compared with the unconditional analysis. Under some regularity conditions, we show that the two estimators are uniformly consistent and converge weakly to...
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作者：Wang, Hao; West, Mike
作者单位：Duke University
摘要：We present Bayesian analyses of matrix-variate normal data with conditional independencies induced by graphical model structuring of the characterizing covariance matrix parameters. This framework of matrix normal graphical models includes prior specifications, posterior computation using Markov chain Monte Carlo methods, evaluation of graphical model uncertainty and model structure search. Extensions to matrix-variate time series embed matrix normal graphs in dynamic models. Examples highligh...
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作者：Fewster, R. M.; Jupp, P. E.
作者单位：University of Auckland; University of St Andrews
摘要：Many models for biological populations, including simple mark-recapture models and distance sampling models, involve a binomially distributed number, n, of observations x(1), ..., x(n) on members of a population of size N. Two popular estimators of (N, theta), where theta is a vector parameter, are the maximum likelihood estimator ((N) over cap, (theta) over cap) and the conditional maximum likelihood estimator ((N) over cap (c) (theta) over cap (c)) based on the conditional distribution of x(...
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作者：Jones, M. C.; Pewsey, Arthur
作者单位：Open University - UK; Universidad de Extremadura
摘要：We introduce the sinh-arcsinh transformation and hence, by applying it to a generating distribution with no parameters other than location and scale, usually the normal, a new family of sinh-arcsinh distributions. This four-parameter family has symmetric and skewed members and allows for tailweights that are both heavier and lighter than those of the generating distribution. The central place of the normal distribution in this family affords likelihood ratio tests of normality that are superio...
