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作者：Ybarra, Lynn M. R.; Lohr, Sharon L.
作者单位：Arizona State University; Arizona State University-Tempe
摘要：Small area estimation methods typically combine direct estimates from a survey with predictions from a model in order to obtain estimates of population quantities with reduced mean squared error. When the auxiliary information used in the model is measured with error, using a small area estimator such as the Fay-Herriot estimator while ignoring measurement error may be worse than simply using the direct estimator. We propose a new small area estimator that accounts for sampling variability in ...
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作者：Guan, Yongtao
作者单位：Yale University
摘要：We introduce a formal testing procedure to assess the fit of an inhomogeneous spatial Poisson process model, based on a discrepancy measure function Dc( t; theta) that is constructed from residuals obtained from the fitted model. We derive the asymptotic distributional properties of Dc( t; theta) and develop a test statistic based on them. Our test statistic has a limiting standard normal distribution, so that the test can be performed by simply comparing the test statistic with readily availa...
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作者：Cook, R. Dennis; Forzani, Liliana
作者单位：University of Minnesota System; University of Minnesota Twin Cities; National University of the Littoral; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
摘要：We introduce covariance reducing models for studying the sample covariance matrices of a random vector observed in different populations. The models are based on reducing the sample covariance matrices to an informational core that is sufficient to characterize the variance heterogeneity among the populations. They possess useful equivariance properties and provide a clear alternative to spectral models for covariance matrices.
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作者：Lin, Pei-Sheng
作者单位：National Chung Cheng University; National Health Research Institutes - Taiwan
摘要：We use the quasilikelihood concept to propose an estimating equation for spatial data with correlation across the study region in a multi-dimensional space. With appropriate mixing conditions, we develop a central limit theorem for a random field under various L-p metrics. The consistency and asymptotic normality of quasilikelihood estimators can then be derived. We also conduct simulations to evaluate the performance of the proposed estimating equation, and a dataset from East Lansing Woods i...
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作者：Qu, Annie; Lee, J. Jack; Lindsay, Bruce G.
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Texas System; UTMD Anderson Cancer Center; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：In the generalized method of moments approach to longitudinal data analysis, unbiased estimating functions can be constructed to incorporate both the marginal mean and the correlation structure of the data. Increasing the number of parameters in the correlation structure corresponds to increasing the number of estimating functions. Thus, building a correlation model is equivalent to selecting estimating functions. This paper proposes a chi-squared test to choose informative unbiased estimating...
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作者：Beyersmann, Jan; Schumacher, Martin
作者单位：University of Freiburg; University of Freiburg
摘要：Nonparametric quantile inference for competing risks has recently been studied by Peng & Fine (2007). Their key result establishes uniform consistency and weak convergence of the inverse of the Aalen-Johansen estimator of the cumulative incidence function, using the representation of the cumulative incidence estimator as a sum of independent and identically distributed random variables. The limit process is of a form similar to that of the standard survival result, but with the cause-specific ...
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作者：Reiter, Jerome P.
作者单位：Duke University
摘要：When some of the records used to estimate the imputation models in multiple imputation are not used or available for analysis, the usual multiple imputation variance estimator has positive bias. We present an alternative approach that enables unbiased estimation of variances and, hence, calibrated inferences in such contexts. First, using all records, the imputer samples m values of the parameters of the imputation model. Second, for each parameter draw, the imputer simulates the missing value...
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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：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：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...
