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作者：Givens, GH; Raftery, AE
作者单位：University of Washington; University of Washington Seattle
摘要：We consider adaptive importance sampling techniques that use kernel density estimates at each iteration as importance sampling functions. These can provide more nearly constant importance weights and more precise estimates of quantities of interest than the sampling importance resampling algorithm when the initial importance sampling function is diffuse relative to the target. We propose a new method that adapts to the varying local structure of the target. When the target has unusual structur...
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作者：Seifert, B; Gasser, T
摘要：Fitting local polynomials in nonparametric regression has a number of advantages. The attractive theoretical features are in a partial contradiction to variance properties for random design and to practical experience over a broad range of situations. No upper bound can be given for the conditional variance. The unconditional variance is infinite when using optimal weights with compact support. Properties are better for Gaussian weights. We analyze local polynomials for finite sample size, bot...
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作者：Jung, SH
摘要：This article proposes quasi-likelihood equations for median regression models. The quasi-likelihood can be used for dependent observations such as repeated measurements or time series data. To construct a quasi-likelihood equation, we need to specify the relation between the median and the dispersion and also specify the dependency of the observations. If a monotone transformation of the original observation has a Laplace distribution, then the quasi-likelihood is the exact likelihood. Under m...
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作者：Severini, TA
摘要：Let Y-1,...,Y-n denote independent real-valued observations, each of the form Y-j = X(j) beta + sigma epsilon(j), where X(j) is a fixed covariate vector, beta and sigma are unknown parameters, and epsilon(1),...,epsilon(n) are identically distributed according to a symmetric density p. This article considers the sensitivity of point estimates of beta to the choice of estimator from classes of estimators based on the L estimators of Kroenker and Portnoy. Specific measures of sensitivity are pro...
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作者：Berger, JO; Pericchi, LR
作者单位：Simon Bolivar University
摘要：In the Bayesian approach to model selection or hypothesis testing with models or hypotheses of differing dimensions, it is typically not possible to utilize standard noninformative (or default) prior distributions. This has led Bayesians to use conventional proper prior distributions or crude approximations to Bayes factors. In this article we introduce a new criterion called the intrinsic Bayes factor, which is fully automatic in the sense of requiring only standard noninformative priors for ...
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作者：Fan, JQ; Hall, P; Martin, MA; Patil, P
作者单位：Australian National University; Australian National University; University of Birmingham
摘要：We develop new local versions of familiar smoothing methods; such as cross-validation and smoothed cross-validation, in the contexts of density estimation and regression. These new methods are locally adaptive in the sense that they capture smooth local fluctuations in the curve by using smoothly varying bandwidths that change as the character of the curve changes. Moreover, the new methods are accurate, easy to apply, and computationally expedient.
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作者：Jones, MC; Marron, JS; Sheather, SJ
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of New South Wales Sydney
摘要：There has been major progress in recent years in data-based bandwidth selection for kernel density estimation. Some ''second generation'' methods, including plug-in and smoothed bootstrap techniques, have been developed that are far superior to well-known ''first generation'' methods, such as rules of thumb, least squares cross-validation, and biased cross-validation. We recommend a ''solve-the-equation'' plug-in bandwidth selector as being most reliable in terms of overall performance. This a...
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作者：Meng, XL; Schilling, S
作者单位：Vanderbilt University
摘要：Based on item response theory, Beck and Aitken introduced a method of item factor analysis, termed full-information item factor (FIIF) analysis by Bartholomew because it uses all distinct item response vectors as data. But a limitation of their fitting algorithm is its reliance on fixed-point Gauss-Hermite quadrature, which can produce appreciable numerical errors, especially in high-dimension problems. The first purpose of this article is to offer more reliable methods by using recent advance...
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作者：Paparoditis, E
摘要：Transfer function models have been used for modeling the linear dependence between stationary time series and for improving the accuracy of forecasts. This article proposes a method to evaluate the fit of such a model by comparing certain frequency domain functionals of the model with those of the data using a model-based bootstrap algorithm. The method works by checking the ability of the fitted model to reproduce the dynamic relationship and the linear dependence structure of the data. Furth...
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作者：Kosorok, MR; Chao, WH
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：A simple Markov model is developed for assessing the predictive effect of time-dependent covariates on an intermittently observed ordinal response in continuous time. This is accomplished by reparameterizing an ergodic intensify matrix in terms of its equilibrium distribution and a parametrically independent component that assesses the rate of movement between ordinal categories. The effect of covariates on the equilibrium distribution can then be modeled using any link appropriate for ordinal...
