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作者：Lin, XH; Wang, NY; Welsh, AH; Carroll, RJ
作者单位：University of Michigan System; University of Michigan; Texas A&M University System; Texas A&M University College Station; University of Southampton; Texas A&M University System; Texas A&M University College Station
摘要：For independent data, it is well known that kernel methods and spline methods are essentially asymptotically equivalent (Silverman, 1984). However, recent work of Welsh et al. (2002) shows that the same is not true for clustered/longitudinal data. Splines and conventional kernels are different in localness and ability to account for the within-cluster correlation. We show that a smoothing spline estimator is asymptotically equivalent to a recently proposed seemingly unrelated kernel estimator ...
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作者：Di Marzio, M; Taylor, CC
作者单位：G d'Annunzio University of Chieti-Pescara; University of Leeds
摘要：This paper proposes an algorithm for boosting kernel density estimates. We show that boosting is closely linked to a previously proposed method of bias reduction and indicate how it should enjoy similar properties. Numerical examples and simulations are used to illustrate the findings, and we also suggest further areas of research.
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作者：Firth, D; De Menezes, RX
作者单位：University of Warwick; Leiden University; Leiden University Medical Center (LUMC); Leiden University - Excl LUMC
摘要：In statistical models of dependence, the effect of a categorical variable is typically described by contrasts among parameters. For reporting such effects, quasi-variances provide an economical and intuitive method which permits approximate inference on any contrast by subsequent readers. Applications include generalised linear models, generalised additive models and hazard models. The present paper exposes the generality of quasi-variances, emphasises the need to control relative errors of ap...
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作者：Samuel-Cahn, E
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作者：Wang, YCJ
作者单位：Rutgers University System; Rutgers University Camden; Rutgers University New Brunswick
摘要：In the Lancaster representation a joint density is decomposed into a sum of additive interactions. Using these interactions, we derive conditions for checking compatibility among a collection of marginal densities. The representation also shows bow to construct an all-positive joint density additively from a given set of compatible marginals. An algorithm is proposed for reducing the dimension of the marginal densities so that compatibility can be checked in sequential increments. The represen...
