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作者：Mizera, I; Müller, CH
作者单位：Comenius University Bratislava; University of Gottingen
摘要：The breakdown point behavior of M-estimators in linear models with fixed designs, arising from planned experiments or qualitative factors, is characterized. Particularly, this behavior at fixed designs is quite different from that at designs which can be corrupted by outliers, the situation prevailing in the literature. For fixed designs, the breakdown points of robust M-estimators (those with bounded derivative of the score function), depend on the design and the variation exponent (index) of...
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作者：Jensen, JL; Petersen, NV
作者单位：Aarhus University
摘要：State space models is a very general class of time series models capable of modelling dependent observations in a natural and interpretable way. Inference in such models has been studied by Bickel, Ritov and Ryden, who consider hidden Markov models, which are special kinds of state space models, and prove that the maximum likelihood estimator is asymptotically normal under mild regularity conditions. In this paper we generalize the results of Bickel, Ritov and Ryden to state space models, wher...
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作者：Dawid, AP; Sebastiani, P
作者单位：University of London; University College London; Open University - UK
摘要：We characterize those coherent design criteria which depend only on the dispersion matrix (assumed proper and nonsingular) of the state of nature, which may be a parameter-vector or a set of future observables, and describe the associated decision problems. Connections are established with the classical approach to optimal design theory for the normal linear model, based on concave functions of the information matrix. Implications of the theory for more general models are also considered.
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作者：Hassairi, A
作者单位：Universite de Sfax; Faculty of Sciences Sfax
摘要：Let mu be a positive measure on R-d and let F(mu) = {P(theta, mu); theta is an element of Theta} be the natural exponential family generated by mu. The aim of this paper is to show that if mu is infinitely divisible then the generalized variance of mu, i.e., the determinant of the covariance operator of P(theta, mu), is the Laplace transform of some positive measure rho(mu) on R-d. We then investigate the effect of the transformation mu --> rho(mu) and its implications for the skewness vector ...
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作者：Tang, BX; Deng, LY
作者单位：University of Memphis
摘要：Deng and Tang proposed generalized resolution and minimum aberration criteria for comparing and assessing nonregular fractional factorials, of which Plackett-Burman designs are special cases. A relaxed variant of generalized aberration is proposed and studied in this paper. We show that a best design according to this criterion minimizes the contamination of nonnegligible interactions on the estimation of main effects in the order of importance given by the hierarchical assumption. The new cri...
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作者：Qin, J
作者单位：University System of Maryland; University of Maryland College Park; Memorial Sloan Kettering Cancer Center
摘要：Pie consider the problem of estimating a mixture proportion using data from two different distributions as well as from a mixture of them. Under the model assumption that the log-likelihood ratio of the two densities is linear in the observations, we develop an empirical likelihood ratio based statistic for constructing confidence intervals for the mixture proportion. Under some regularity conditions, it is shown that this statistic converges to a chi-squared random variable. Simulation result...
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作者：Hsing, T
作者单位：National University of Singapore; Texas A&M University System; Texas A&M University College Station
摘要：Sliced inverse regression (SIR), formally introduced by Li, is a very general procedure for performing dimension reduction in nonparametric regression. This paper considers a version of SIR in which the slices are determined by nearest neighbors and the response variable takes value possibly in a multidimensional space. It is shown, under general conditions, that the effective dimension reduction space can be estimated with rate n(-1/2) where n is the sample size.
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作者：Bai, ZD; He, XM
作者单位：National University of Singapore; University of Illinois System; University of Illinois Urbana-Champaign
摘要：We derive the asymptotic distribution of the maximal depth regression estimator recently proposed in Rousseeuw and Hubert. The estimator is obtained by maximizing a projection-based depth and the limiting distribution is characterized through a max-min operation of a continuous process. The same techniques can be used to obtain the limiting distribution of some other depth estimators including Tukey's deepest point based on half-space depth. Results for the special case of two-dimensional prob...
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作者：Huang, J
作者单位：University of Iowa
摘要：The partly linear additive Cox model is an extension of the (linear) Cox model and allows flexible modeling of covariate effects; semiparametrically. We study asymptotic properties of the maximum partial likelihood estimator of this model with right-censored data using; polynomial splines. We show that, with a range of choices of the smoothing parameter (the number of spline basis functions) required for estimation of the nonparametric components, the estimator of the finite-dimensional regres...
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作者：Liang, H; Härdle, W; Carroll, RJ
作者单位：Chinese Academy of Sciences; Humboldt University of Berlin; Texas A&M University System; Texas A&M University College Station
摘要：We consider the partially linear model relating a response Y to predictors (X,T) with mean function X(inverted perpendicular)beta + g(T) when the X's are measured with additive error. The semiparametric likelihood estimate of Severini and Staniswalis leads to biased estimates of both the parameter beta and the function g((.))when measurement error is ignored. We derive a simple modification of their estimator which is a semiparametric version of the usual parametric correction for attenuation....
