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作者：Fuh, CD; Hu, I
作者单位：Academia Sinica - Taiwan; Hong Kong University of Science & Technology
摘要：We propose a method for finding the alternative distribution in importance sampling. The alternative distribution is optimal in the sense that the asymptotic variance is minimised for estimating tail probabilities of asymptotically normal statistics. Our contribution to importance sampling is three-fold. To begin with, we obtain an explicit expression for the mean of the optimal alternative distribution and the expression motivates a recursive approximation algorithm. Secondly, a new multi-dim...
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作者：Qu, A; Song, PXK
作者单位：Oregon State University; York University - Canada
摘要：In the presence of data contamination or outliers, some empirical studies have indicated that the two methods of generalised estimating equations and quadratic inference functions appear to have rather different robustness behaviour. This paper presents a theoretical investigation from the perspective of the influence function to identify the causes for the difference. We show that quadratic inference functions lead to bounded influence functions and the corresponding M-estimator has a redesce...
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作者：Ghosh, M; Maiti, T
作者单位：State University System of Florida; University of Florida; Iowa State University
摘要：We propose pseudo empirical best linear unbiased estimators of small-area means based on natural exponential family quadratic variance function models when the basic data consist of survey-weighted estimators of these means, area-specific covariates and certain summary measures involving the weights. We also provide explicit approximate mean squared errors of these estimators in the spirit of Prasad & Rao (1990), and these estimators can be readily evaluated. A simulation study is undertaken t...
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作者：Craiu, RV; Duchesne, T
作者单位：University of Toronto; Laval University
摘要：In this paper we propose inference methods based on the Em algorithm for estimating the parameters of a weakly parameterised competing risks model with masked causes of failure and second-stage data. With a carefully chosen definition of complete data, the maximum likelihood estimation of the cause-specific hazard functions and of the masking probabilities is performed via an Em algorithm. Both the E- and m-steps can be solved in closed form under the full model and under some restricted model...
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作者：Dette, H; Kwiecien, R
作者单位：Ruhr University Bochum; RWTH Aachen University
摘要：Classical regression analysis is usually performed in two steps. In a first step an appropriate model is identified to describe the data-generating process and in a second step statistical inference is performed in the identified model. In this paper we investigate a sequential and a non-sequential design strategy, which take into account these different goals of the analysis for a class of nested models. It is demonstrated that non-sequential designs usually identify the 'correct' model with ...
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作者：Liechty, JC; Liechty, MW; Müller, P
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Drexel University; University of Texas System; UTMD Anderson Cancer Center
摘要：We propose prior probability models for variance-covariance matrices in order to address two important issues. First, the models allow a researcher to represent substantive prior information about the strength of correlations among a set of variables. Secondly, even in the absence of such information, the increased flexibility of the models mitigates dependence on strict parametric assumptions in standard prior models. For example, the model allows a posteriori different levels of uncertainty ...
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作者：Deville, JC; Tillé, Y
作者单位：Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI); University of Neuchatel
摘要：A balanced sampling design is defined by the property that the Horvitz-Thompson estimators of the population totals of a set of auxiliary variables equal the known totals of these variables. Therefore the variances of estimators of totals of all the variables of interest are reduced, depending on the correlations of these variables with the controlled variables. In this paper, we develop a general method, called the cube method, for selecting approximately balanced samples with equal or unequa...
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作者：Rao, SS
作者单位：Ruprecht Karls University Heidelberg
摘要：We consider the estimation of parameters of a multiple regression model with nonstationary errors. We assume the nonstationary errors satisfy a time-dependent autoregressive process and describe a method for estimating the parameters of the regressors and the time-dependent autoregressive parameters. The parameters are rescaled as in nonparametric regression to obtain the asymptotic sampling properties of the estimators. The method is illustrated with an example taken from global temperature a...
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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：Joseph, VR
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：The Robbins-Monro procedure does not perform well in the estimation of extreme quantiles, because the procedure is implemented using asymptotic results, which are not suitable for binary data. Here we propose a modification of the Robbins-Monro procedure and derive the optimal procedure for binary data under some reasonable approximations. The improvement obtained by using the optimal procedure for the estimation of extreme quantiles is substantial.
