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作者：Cifarelli, DM; Conti, PL; Regazzini, E
作者单位：Consiglio Nazionale delle Ricerche (CNR); Sapienza University Rome
摘要：In this paper the asymptotic normality of a class of statistics, including Gini's index of cograduation and Spearman's rank correlation coefficient, is proved. The asymptotic normality is stated under a large class of alternatives including the bivariate distributions corresponding to a condition of lack of association introduced in Section 3. The problems of testing the hypothesis of lack of association and of constructing confidence intervals for the population index of cograduation are also...
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作者：Maa, JF; Pearl, DK; Bartoszynski, R
作者单位：University System of Ohio; Ohio State University
摘要：The most popular technique for reducing the dimensionality in comparing two multidimensional samples of X similar to F and Y similar to G is to analyze distributions of interpoint comparisons based on a univariate function h (e.g. the interpoint distances). We provide a theoretical foundation for this technique, by showing that having both i) the equality of the distributions of within sample comparisons (h(X(1),X(2)) =(L) h(Y-1,Y-2)) and ii) the equality of these with the distribution of betw...
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作者：Wang, JD
摘要：This paper is devoted do studying the asymptotic behavior of LS-estimators in constrained nonlinear regression problems. Here the constraints are given by nonlinear equalities and inequalities. Thus this is a very general setting. Essentially this kind of estimation problem is a stochastic optimization problem. So we make use of methods in optimization to overcome the difficulty caused by nonlinearity in the regression model and given constraints.
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作者：Rocke, DM
摘要：For the problem of robust estimation of multivariate location and shape, defining S-estimators using scale transformations of a fixed rho function regardless of the dimension, as is usually done, leads to a perverse outcome: estimators in high dimension can have a breakdown point approaching 50%, but still fail to reject as outliers points that are large distances from the main mass of points. This leads to a form of nonrobustness that has important practical consequences. In this paper, estim...
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作者：Zhu, LX; Fang, KT
作者单位：Hong Kong Baptist University
摘要：To explore nonlinear structures hidden in high-dimensional data and to estimate the effective dimension reduction directions in multivariate nonparametric regression, Li and Duan proposed the sliced inverse regression (SIR) method which is simple to use. In this paper, the asymptotic properties of the kernel estimate of sliced inverse regression are investigated. It turns out that regardless of the kernel function, the asymptotic distribution remains the same for a wide range of smoothing para...
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作者：Koul, HL; Schick, A
作者单位：State University of New York (SUNY) System; Binghamton University, SUNY
摘要：This paper proves the local asymptotic normality of a stationary and ergodic first order random coefficient autoregressive model in a semiparametric setting. This result is used to show that Stein's necessary condition for adaptive estimation of the mean of the random coefficient is satisfied if the distributions of the innovations and the errors in the random coefficients are symmetric around zero. Under these symmetry assumptions, a locally asymptotically minimax adaptive estimator of the me...
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作者：Liu, JS
摘要：We consider the empirical Bayes estimation of a distribution using binary data via the Dirichlet process. Let D(alpha) denote a Dirichlet process with alpha being a finite measure on [0, 1]. Instead of having direct samples from an unknown random distribution F from D(alpha), we assume that only indirect binomial data are observable. This paper presents a new interpretation of Lo's formula, and thereby relates the predictive density of the observations based on a Dirichlet process model to lik...
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作者：Li, B
摘要：The consistency of estimating equations has been studied, in the main, along the lines of Cramer's classical argument, which only asserts the existence of consistent solutions. The statement similar to that of Doob and Weld, which identifies the consistent solutions, has not yet been established. The obstacle is that the solutions of estimating equations cannot in general be defined as the maximum of likelihood functions. In this paper we demonstrate that the consistent solutions can be identi...
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作者：Dette, H
作者单位：Technische Universitat Dresden
摘要：We present a version of Elfving's theorem for the Bayesian D-optimality criterion in nonlinear regression models. The Bayesian optimal design can be characterized as a design which allows a representation of a (uniquely determined) boundary point of a convex subset of L(2)-integrable functions. A similar characterization is given for the Bayesian c-optimality criterion where a (possible) nonlinear function of the unknown parameters has to be estimated. The results are illustrated in the exampl...
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作者：Hess, C
摘要：Using the variational properties of epi-convergence together with suitable results on the measurability of multifunctions and integrands, we prove a strong law of large numbers for sequences of integrands from which we deduce a general theorem of almost sure convergence (strong consistency) for the maximum likelihood estimator.
