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作者：Li, G; Tiwari, RC; Wells, MT
作者单位：University of California System; University of California Los Angeles; University of North Carolina; University of North Carolina Charlotte; Cornell University
摘要：In studies to compare two samples, more information may be available on one treatment than the other. When one population is modelled parametrically and the other nonparametrically, we study large sample properties of a semiparametric sample quantile comparison function and show that it can have substantially smaller asymptotic variance than its nonparametric counterpart, especially near the boundaries. We describe applications to both two-sample tests and receiver operating characteristic cur...
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作者：Newton, MA; Zhang, YL
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：The mixture of Dirichlet processes posterior that arises in nonparametric Bayesian analysis has been analysed most effectively using Markov chain Monte Carlo. As a computationally simple alternative, we introduce a recursive approximation based on one-step posterior predictive distributions. Asymptotic calculations provide theoretical support for this approximation, and we investigate its actual behaviour in several numerical examples. From a non-Bayesian perspective, this new recursion may be...
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作者：Hjellvik, V; Tjostheim, D
作者单位：Institute of Marine Research - Norway; University of Bergen
摘要：We propose a method of modelling panel time series: data with both inter- and intraindividual correlation, and of fitting an autoregressive model to such data. Estimators are obtained by a conditional likelihood argument. If there are few observations in each series, the estimators can be dramatically improved by Burg-type:estimators taking edge effects into account. The consequences of ignoring the intercorrelation term are analysed. Partial lack of consistency is demonstrated in this situati...
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作者：Cavanaugh, JE; Johnson, WO
作者单位：University of Missouri System; University of Missouri Columbia; University of California System; University of California Davis
摘要：An important inferential objective in state space modelling is to recover unobserved states using fixed-interval smoothing. Thus, the identification of cases which have a substantial influence on the smoothers is a relevant practical problem. To facilitate this identification, we propose a case-deletion diagnostic which can be easily computed using the outputs of the standard filtering and smoothing algorithms. Our diagnostic is defined as the Kullback-Leibler directed divergence between two v...
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作者：Lee, SMS; Young, GA
作者单位：University of Hong Kong; University of Cambridge
摘要：We consider construction of two-sided nonparametric confidence intervals in a smooth function model setting. A nonparametric likelihood approach based on Stein's least favourable family is proposed as an alternative to empirical likelihood. The approach enjoys the same asymptotic:properties as empirical likelihood, but is analytically and computationally less cumbersome. The simplicity of the method allows us to propose and analyse asymptotic and bootstrapping techniques as a means of reducing...
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作者：Dykstra, R; Hewett, J; Robertson, T
作者单位：University of Iowa; University of Missouri System; University of Missouri Columbia
摘要：In many situations it is desirable that prediction/discriminant rules should satisfy ordering properties with respect to the explanatory variables. Here, optimal rules under both L-1 and L-2 type loss functions are characterised under the restriction that the rules be isotonic with respect to the partial ordering on the explanatory variables. An example is given where college grade-point average is predicted based upon high school rank and American College Testing scores.
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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：Bühlmann, P
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：We propose a dynamic adaptive partitioning scheme for nonparametric analysis of stationary nonlinear time series. It yields estimates of the whole probability distribution of the :underlying process. We use information from past values to construct adaptive partitioning in a dynamic fashion which is then different-from the more common static schemes-in the regression set-up. The idea of dynamic partitioning is new. We make it constructive by an approach based on quantisation of the data and ad...
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作者：Gu, MG; Follmann, D; Geller, NL
作者单位：Chinese University of Hong Kong; National Institutes of Health (NIH) - USA; NIH National Heart Lung & Blood Institute (NHLBI)
摘要：This paper considers a general class of statistics for testing the equality of two survival distributions in clinical trials with sequential monitoring. The tests can be expressed as Lebesgue-Stieltjes integrals of a weight function with respect to the difference between two survival distributions. Prominent members of this class include the two-sample difference in Kaplan-Meier estimates, the test of medians (Brookmeyer & Crowley, 1982), a truncated version of Efron's (1967) test and the Pepe...
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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...
