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作者：Wang, XG; Zidek, JV
作者单位：York University - Canada; University of British Columbia
摘要：The (relevance) weighted likelihood was introduced to formally embrace a variety of statistical procedures that trade bias for precision. Unlike its classical counterpart, the weighted likelihood combines all relevant information while inheriting many of its desirable features including good asymptotic properties. However, in order to be effective, the weights involved in its construction need to be judiciously chosen. Choosing those weights is the subject of this article in which we demonstra...
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作者：McCullagh, P
作者单位：University of Chicago
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作者：Xu, HQ; Wu, CFJ
作者单位：University of California System; University of California Los Angeles; University System of Georgia; Georgia Institute of Technology
摘要：A supersaturated design is a design whose run size is not large enough for estimating all the main effects. The goodness of multi-level supersaturated designs can be judged by the generalized minimum aberration criterion proposed by Xu and Wu [Ann. Statist. 29 (2001) 1066-1077]. A new lower bound is derived and general construction methods are proposed for multi-level supersaturated designs. Inspired by the Addelman-Kempthorne construction of orthogonal arrays, several classes of optimal multi...
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作者：Jaeger, M
作者单位：Aalborg University
摘要：We study the problem of ignorability in likelihood-based inference from incomplete categorical data. Two versions of the coarsened at random assumption (car) are distinguished, their compatibility with the parameter distinctness assumption is investigated and several conditions for ignorability that do not require an extra parameter distinctness assumption are established. It is shown that car assumptions have quite different implications depending on whether the underlying complete-data model...
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作者：Genton, MG; Lucas, A
作者单位：Texas A&M University System; Texas A&M University College Station; Vrije Universiteit Amsterdam
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作者：Lin, PS; Clayton, MK
作者单位：National Chung Cheng University; University of Wisconsin System; University of Wisconsin Madison
摘要：The goal of this paper is to describe the application of quasi-likelihood estimating equations for spatially correlated binary data. In this paper, a logistic function is used to model the marginal probability of binary responses in terms of parameters of interest. With mild assumptions on the correlations, the Leonov-Shiryaev formula combined with a comparison of characteristic functions can be used to establish asymptotic normality for linear combinations of the binary responses. The consist...
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作者：Jupp, PE
作者单位：University of St Andrews
摘要：Classes of coordinate-invariant omnibus goodness-of-fit tests on compact Riemannian manifolds are proposed. The tests are based on Gine's Sobolev tests of uniformity. A condition for consistency is given. The tests are illustrated by an example on the rotation group SO(3).
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作者：Mammen, E; Park, BU
作者单位：University of Mannheim; Seoul National University (SNU)
摘要：The smooth backfitting introduced by Marnmen, Linton and Nielsen [Ann. Statist. 27 (1999) 1443-1490] is a promising technique to fit additive regression models and is known to achieve the oracle efficiency bound. In this paper, we propose and discuss three fully automated bandwidth selection methods for smooth backfitting in additive models. The first one is a penalized least squares approach which is based on higher-order stochastic expansions for the residual sums of squares of the smooth ba...
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作者：Balan, RM; Schiopu-Kratina, I
作者单位：University of Ottawa; Statistics Canada
摘要：We consider the marginal models of Liang and Zeger [Bioinetrika 73 (1986) 13-22] for the analysis of longitudinal data and we develop a theory of statistical inference for such models. We prove the existence, weak consistency and asymptotic normality of a sequence of estimators defined as roots of pseudo-likelihood equations.
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作者：Cheng, CS; Tang, BX
作者单位：Academia Sinica - Taiwan; University of California System; University of California Berkeley; Simon Fraser University; University of Memphis
摘要：Minimum aberration is an increasingly popular criterion for comparing and assessing fractional factorial designs, and few would question its importance and usefulness nowadays. In the past decade or so, a great deal of work has been done on minimum aberration and its various extensions. This paper develops a general theory of minimum aberration based on a sound statistical principle. Our theory provides a unified framework for minimum aberration and further extends the existing work in the are...
