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作者：Zhu, Zhongyi; Fung, Wing K.; He, Xuming
作者单位：Fudan University; University of Hong Kong; University of Illinois System; University of Illinois Urbana-Champaign
摘要：There have been studies on how the asymptotic efficiency of a nonparametric function estimator depends on the handling of the within-cluster correlation when nonparametric regression models are used on longitudinal or cluster data. In particular, methods based on smoothing splines and local polynomial kernels exhibit different behaviour. We show that the generalized estimation equations based on weighted least squares regression splines for the nonparametric function have an interesting proper...
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作者：Nedyalkova, Desislava; Tille, Yves
作者单位：University of Neuchatel
摘要：In some cases model-based and model-assisted inferences can lead to very different estimators. These two paradigms are not so different if we search for an optimal strategy rather than just an optimal estimator, a strategy being a pair composed of a sampling design and an estimator. We show that, under a linear model, the optimal model-assisted strategy consists of a balanced sampling design with inclusion probabilities that are proportional to the standard deviations of the errors of the mode...
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作者：Kuang, D.; Nielsen, B.; Nielsen, J. P.
作者单位：University of Oxford; University of Oxford; City St Georges, University of London
摘要：We consider the identification problem that arises in the age-period-cohort models as well as in the extended chain-ladder model. We propose a canonical parameterization based on the accelerations of the trends in the three factors. This parameterization is exactly identified and eases interpretation, estimation and forecasting. The canonical parameterization is applied to a class of index sets which have trapezoidal shapes, including various Lexis diagrams and the insurance-reserving triangles.
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作者：Westfall, Peter H.
作者单位：Texas Tech University System; Texas Tech University
摘要：Benjamini and Hochberg's method for controlling the false discovery rate is applied to the problem of testing infinitely many contrasts in linear models. Exact, easily calculated critical values are derived, defining a new multiple comparisons method for testing contrasts in linear models. The method is adaptive, depending on the data through the F-statistic, like the Waller-Duncan Bayesian multiple comparisons method. Comparisons with Scheffe's method are given, and the method is extended to ...
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作者：Kim, Sungduk; Chen, Ming-Hui; Dey, Dipak K.
作者单位：University of Connecticut
摘要：A critical issue in modelling binary response data is the choice of the links. We introduce a new link based on the generalized t-distribution. There are two parameters in the generalized t-link: one parameter purely controls the heaviness of the tails of the link and the second parameter controls the scale of the link. Two major advantages are offered by the generalized t-links. First, a symmetric generalized t-link with an unknown shape parameter is much more identifiable than a Student t-li...
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作者：Li, Bo; Genton, Marc G.; Sherman, Michael
作者单位：Purdue University System; Purdue University; Texas A&M University System; Texas A&M University College Station
摘要：There is an increasing wealth of multivariate spatial and multivariate spatio-temporal data appearing. For such data, an important part of model building is an assessment of the properties of the underlying covariance function describing variable, spatial and temporal correlations. In this paper, we propose a methodology to evaluate the appropriateness of several types of common assumptions on multivariate covariance functions in the spatio-temporal context. The methodology is based on the asy...
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作者：Dryden, Ian L.; Kume, Alfred; Le, Huiling; Wood, Andrew T. A.
作者单位：University of Nottingham; University of Kent
摘要：We propose an alternative to Kendall's shape space for reflection shapes of configurations in Rm with k labelled vertices, where reflection shape consists of all the geometric information that is invariant under compositions of similarity and reflection transformations. The proposed approach embeds the space of such shapes into the space P( k - 1) of ( k - 1) x ( k - 1) real symmetric positive semidefinite matrices, which is the closure of an open subset of a Euclidean space, and defines mean ...
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作者：Dunson, David B.; Peddada, Shyamal D.
作者单位：Duke University; National Institutes of Health (NIH) - USA; NIH National Institute of Environmental Health Sciences (NIEHS)
摘要：We consider Bayesian inference about collections of unknown distributions subject to a partial stochastic ordering. To address problems in testing of equalities between groups and estimation of group-specific distributions, we propose classes of restricted dependent Dirichlet process priors. These priors have full support in the space of stochastically ordered distributions, and can be used for collections of unknown mixture distributions to obtain a flexible class of mixture models. Theoretic...
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作者：Li, Yingxing; Ruppert, David
作者单位：Cornell University; Cornell University
摘要：We study the asymptotic behaviour of penalized spline estimators in the univariate case. We use B-splines and a penalty is placed on mth-order differences of the coefficients. The number of knots is assumed to converge to infinity as the sample size increases. We show that penalized splines behave similarly to Nadaraya - Watson kernel estimators with 'equivalent' kernels depending upon m. The equivalent kernels we obtain for penalized splines are the same as those found by Silverman for smooth...
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作者：Yu, Zhangsheng; Lin, Xihong
作者单位：University System of Ohio; Ohio State University; Harvard University; Harvard T.H. Chan School of Public Health
摘要：We study nonparametric regression for correlated failure time data. Kernel estimating equations are used to estimate nonparametric covariate effects. Independent and weighted-kernel estimating equations are studied. The derivative of the nonparametric function is first estimated and the nonparametric function is then estimated by integrating the derivative estimator. We show that the nonparametric kernel estimator is consistent for any arbitrary working correlation matrix and that its asymptot...
