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作者：Dümbgen, L
作者单位：University of Lubeck
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作者：Taupin, ML
作者单位：Universite Paris Saclay; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI)
摘要：In the nonlinear structural errors-in-variables model, we propose a consistent estimator of the unknown parameter using a modified least squares criterion. We give an upper bound of its rate of convergence which is strongly related to the regularity of the regression function and is generally slower than the parametric rate of convergence n(-1/2). Nevertheless, the rate is of order n-(1/2) for some particular analytic regression functions. For instance, when the regression Function is either a...
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作者：Goldenshluger, A; Tsybakov, A
作者单位：University of Haifa; Sorbonne Universite
摘要：The problem of adaptive prediction and estimation in the stochastic linear regression model with infinitely many parameters is considered. We suggest a prediction method that is sharp asymptotically minimax adaptive over ellipsoids in l(2). The method consists in an application of blockwise Stein's rule with weakly geometrically increasing blocks to the penalized least squares fits of the first N coefficients. To prove the results we develop oracle inequalities for a sequence model with correl...
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作者：Chang, T; Rivest, LP
作者单位：University of Virginia; Laval University
摘要：We discuss here a general approach to the calculation of the asymptotic covariance of M-estimates for location parameters in statistical group models when an invariant objective function is used. The calculation reduces to standard tools in group representation theory and the calculation of some constants. Only the constants depend upon the precise forms of the density or of the objective function. If the group is sufficiently large this represents a major simplification in the computation of ...
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作者：Einmahl, JHJ; De Haan, L; Piterbarg, VI
作者单位：Tilburg University; Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University Rotterdam; Lomonosov Moscow State University
摘要：Let (X-1, Y-1),..., (X-n, Y-n) be a random sample from a bivariate distribution function F in the domain of max-attraction of a distribution function G. This G is characterised by the two extreme value indices and its spectral or angular measure. The extreme value indices determine both the marginals and the spectral measure determines the dependence structure of G. One of the main issues in multivariate extreme value theory is the estimation of this spectral measure. We construct a truly nonp...
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作者：Benjamini, Y; Yekutieli, D
作者单位：Tel Aviv University
摘要：Benjamini and Hochberg suggest that the false discovery rate may be the appropriate error rate to control in many applied multiple testing problems. A simple procedure was given there as an FDR controlling procedure for independent test statistics and was shown to be much more powerful than comparable procedures which control the traditional family wise error rate. We prove that this same procedure also controls the false discovery rate when the test statistics have positive regression depende...
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作者：Groeneboom, P; Jongbloed, G; Wellner, JA
作者单位：Delft University of Technology; Vrije Universiteit Amsterdam; University of Washington; University of Washington Seattle
摘要：We study nonparametric estimation of convex regression and density functions by methods of least squares (in the regression and density cases) and maximum likelihood (in the density estimation case). We provide characterizations of these estimators, prove that they are consistent and establish their asymptotic distributions at a fixed point of positive curvature of the functions estimated. The asymptotic distribution theory relies on the existence of an invelope function for integrated two-sid...
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作者：Spruill, MC; Tu, R
作者单位：University System of Georgia; Georgia Institute of Technology; University System of Georgia; Columbus State University
摘要：Design measures maximizing local power of asymptotically uniformly most powerful (AUMP) tests about the value of logit P outside the observation space are characterized.
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作者：Hristache, M; Juditsky, A; Spokoiny, V
作者单位：Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI); Institut Polytechnique de Paris; ENSAE Paris; Communaute Universite Grenoble Alpes; Universite Grenoble Alpes (UGA); Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics
摘要：Single-index modeling is widely applied in, for example, econometric studies as a compromise between too restrictive parametric models and flexible but hardly estimable purely nonparametric, models. By such modeling the statistical analysis usually focuses on estimating the index coefficients. The average derivative estimator (ADE) of the index vector is based on the fact that the average gradient of a single index function f(x(T)beta) is proportional to the index vector beta. Unfortunately, a...
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作者：Drees, H
作者单位：Ruprecht Karls University Heidelberg
摘要：Asymptotic minimax risk bounds for estimators of a positive extreme value index under zero-one loss are investigated in the classical i.i.d. setup. To this end, we prove the weak convergence of suitable local experiments with Pareto distributions as center of localization to a white noise model, which was previously studied in the context of nonparametric local density estimation and regression. From this result we derive upper and lower bounds on the asymptotic minimax risk in the local and i...
