2005

最新文章

• Ignorability for categorical data AI翻译
  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...
• Breakdown and groups - Discussion AI翻译
  作者：Genton, MG; Lucas, A
  作者单位：Texas A&M University System; Texas A&M University College Station; Vrije Universiteit Amsterdam
• Analysis of binary spatial data by quasi-likelihood estimating equations AI翻译
  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...
• Sobolev tests of goodness of fit of distributions on compact Riemannian manifolds AI翻译
  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).
• Bandwidth selection for smooth backfitting in additive models AI翻译
  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...
• Asymptotic results with generalized estimating equations for longitudinal data AI翻译
  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.
• A general theory of minimum aberration and its applications AI翻译
  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...
• Confidence sets for nonparametric wavelet regression AI翻译
  作者：Genovese, CR; Wasserman, L
  作者单位：Carnegie Mellon University
  摘要：We construct nonparametric confidence sets for regression functions using wavelets that are uniform over Besov balls. We consider both thresholding and modulation estimators for the wavelet coefficients. The confidence set is obtained by showing that a pivot process, constructed from the loss function, converges uniformly to a mean zero Gaussian process. Inverting this pivot yields a confidence set for the wavelet coefficients, and from this we obtain confidence sets on functionals of the regr...
• Exact local Whittle estimation of fractional integration AI翻译
  作者：Shimotsu, K; Phillips, PCB
  作者单位：Queens University - Canada; Yale University
  摘要：An exact form of the local Whittle likelihood is studied with the intent of developing a general-purpose estimation procedure for the memory parameter (d) that does not rely on tapering or differencing prefilters. The resulting exact local Whittle estimator is shown to be consistent and to have the same N(0, (1)/(4)) limit distribution for all values of d if the optimization covers an interval of width less than (9)/(2) and the initial value of the process is known.
• Optimal smoothing in nonparametric mixed-effect models AI翻译
  作者：Gu, C; Ma, P
  作者单位：Purdue University System; Purdue University; Harvard University
  摘要：Mixed-effect models are widely used for the analysis of correlated data such as longitudinal data and repeated measures. In this article, we study an approach to the nonparametric estimation of mixed-effect models. We consider models with parametric random effects and flexible fixed effects, and employ the penalized least squares method to estimate the models. The issue to be addressed is the selection of smoothing parameters through the generalized cross-validation method, which is shown to y...