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作者：Wikle, CK; Cressie, N
作者单位：University of Missouri System; University of Missouri Columbia; University System of Ohio; Ohio State University
摘要：Many physical/biological processes involve variability over both space and time. As a result of difficulties caused by large datasets and the modelling of space, time and spatiotemporal interactions, traditional space-time methods are limited. In this paper, we present an approach to space-time prediction that achieves dimension reduction and uses a statistical model that is temporally dynamic and spatially descriptive. That is, it exploits the unidirectional flow of time, in an autoregressive...
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作者：Hall, P; Peng, L; Tajvidi, N
作者单位：Australian National University; Linkoping University
摘要：We argue that prediction intervals based on predictive likelihood do not correct for curvature with respect to the parameter value when they implicitly approximate an unknown probability density. Partly as a result of this difficulty, the order of coverage error associated with predictive intervals and predictive limits is equal to only the inverse of sample size. In this respect those methods do not improve on the simpler,'naive' or 'estimative' approach. Moreover, in cases of practical impor...
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作者：Kosorok, MR
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：A simple, nonparametric two-sample test for equality of a given collection of quantiles is developed which can be applied to a variety of empirical distribution functions, including the Kaplan-Meier estimator, a self-consistent estimator for doubly-censored data and an estimator for repeated measures data. The null hypothesis tested is that the quantiles are equal but other aspects of the distributions may differ between the two samples. This procedure can also be applied to quantile testing i...
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作者：Chen, K; Lo, SH
作者单位：Hong Kong University of Science & Technology; Columbia University
摘要：Prentice (1986) proposed the case-cohort design and studied a pseudolikelihood estimator of regression parameters in Cox's model. We derive a class of estimating equations for case-cohort sampling, each depending on a different estimator of the population distribution, which lead naturally to simple estimators that improve on Prentice's pseudolikelihood estimator. We also discuss an equivalence between case-control and case-cohort sampling in terms of the estimation of regression parameters in...
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作者：Xia, YC; Tong, H; Li, WK
作者单位：University of Hong Kong
摘要：Aiming to explore the relation between the response y and the stochastic explanatory vector variable X beyond the linear approximation, we consider the single-index model, which is a well-known approach in multidimensional cases. Specifically, we extend the partially linear single-index model to take the from y = beta(0)(T)X + phi(theta(0)(T)X) + epsilon, where epsilon is a random variable with E epsilon = 0 and var(epsilon)= sigma(2), unknown, beta(0) and theta(0) are unknown parametric vecto...
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作者：Skouras, K; Dawid, AP
作者单位：University of London; University College London
摘要：We study the asymptotic behaviour of probability forecasting systems, and discuss their usefulness as inferential tools for statistical problems such as model verification and selection. Our theoretical setting is the prequential, or predictive sequential, framework proposed by Dawid (1984). We study especially the notion of prequential efficiency of a forecasting system and present some new results. We focus on plug-in, or estimative, forecasting systems, where the forecast distribution is ge...
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作者：Choi, E; Hall, P
作者单位：Australian National University
摘要：We introduce a data-perturbation method for reducing bias of a wide variety of density estimators, in univariate, multivariate spatial and spherical data settings. The method involves 'sharpening' the data by making them slightly more clustered than before, and then computing the estimator in the usual way, but from the sharpened data rather than the original data. The transformation depends in a simple, explicit way on the smoothing parameter employed for the density estimator, which may be b...
