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作者：Qi, Xin; Zhao, Hongyu
作者单位：Yale University
摘要：Ordinary differential equations (ODEs) are commonly used to model dynamic behavior of a system. Because many parameters are unknown and have to be estimated from the observed data, there is growing interest in statistics to develop efficient estimation procedures for these parameters. Among the proposed methods in the literature, the generalized profiling estimation method developed by Ramsay and colleagues is particularly promising for its computational efficiency and good performance. In thi...
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作者：Rousseau, Judith
作者单位：Universite PSL; Universite Paris-Dauphine
摘要：In this paper, we investigate the asymptotic properties of nonparametric Bayesian mixtures of Betas for estimating a smooth density on [0, 1]. We consider a parametrization of Beta distributions in terms of mean and scale parameters and construct a mixture of these Betas in the mean parameter, while putting a prior on this scaling parameter. We prove that such Bayesian nonparametric models have good frequentist asymptotic properties. We determine the posterior rate of concentration around the ...
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作者：Evans, Michael; Jang, Gun Ho
作者单位：University of Toronto
摘要：P-values have been the focus of considerable criticism based on various considerations. Still, the P-value represents one of the most commonly used statistical tools. When assessing the suitability of a single hypothesized distribution, it is not clear that there is a better choice for a measure of surprise. This paper is concerned with the definition of appropriate model-based P-values for model checking.
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作者：Golubev, Georgi K.; Nussbaum, Michael; Zhou, Harrison H.
作者单位：Aix-Marseille Universite; Cornell University; Yale University
摘要：We consider the statistical experiment given by a sample y(l),...,y(n) of a stationary Gaussian process with an unknown smooth spectral density f. Asymptotic equivalence, in the sense of Le Cam's deficiency Delta-distance, to two Gaussian experiments with simpler structure is established. The first one is given by independent zero mean Gaussians with variance approximately f(omega(i)), where omega(i) is a uniform grid of points in (-pi, pi) (nonparametric Gaussian scale regression). This appro...
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作者：Jacob, Christine
作者单位：INRAE; Universite Paris Saclay
摘要：Let {Z(n)} be a real nonstationary stochastic process such that E(Z(n)vertical bar Fn-1) <(a.s.) infinity and E(Z(n)(2)vertical bar Fn-1) <(a.s.) infinity, where {F-n} is an increasing sequence of sigma-algebras. Assuming that E(Z(n)vertical bar Fn-1) = gn(theta(0), nu(0)) = g(n)((1))(theta(0)) + g(n)((2))(theta(0), nu(0)), theta(0) is an element of R-p, p < infinity, nu(0) is an element of R-q and q <= infinity, we study the symptotic properties of <(theta)over cap>(n) := arg min(theta) Sigma...
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作者：Romano, Joseph P.; Wolf, Michael
作者单位：Stanford University; Stanford University; University of Zurich
摘要：Consider the problem of testing s hypotheses simultaneously. In this paper, we derive methods which control the generalized family-wise error rate given by the probability of k or more false rejections, abbreviated k-FWER. We derive both single-step and step-down procedures that control the k-FWER in finite samples or asymptotically, depending on the situation. Moreover, the procedures are asymptotically balanced in an appropriate sense. We briefly consider control of the average number of fal...
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作者：Mendelson, Shahar; Neeman, Joseph
作者单位：Australian National University; Technion Israel Institute of Technology; University of California System; University of California Berkeley
摘要：Under mild assumptions on the kernel, we obtain the best known error rates in a regularized learning scenario taking place in the corresponding reproducing kernel Hilbert space (RKHS). The main novelty in the analysis is a proof that one can use a regularization term that grows significantly slower than the standard quadratic growth in the RKHS norm.
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作者：Klemela, Jussi; Mammen, Enno
作者单位：University of Oulu; University of Mannheim
摘要：We study estimation of a multivariate function f : R-d -> R when the observations are available from the function Af. where A is a known linear operator. Both the Gaussian white noise model and density estimation are studied. We define an L-2-empirical risk functional which is used to define a delta-net minimizer and a dense empirical risk minimizer. Upper bounds for the mean integrated squared error of the estimators are given. The upper bounds show how the difficulty of the estimation depend...
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作者：Arlot, Sylvain; Blanchard, Gilles; Roquain, Etienne
作者单位：Universite PSL; Ecole Normale Superieure (ENS); Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Information Sciences & Technologies (INS2I); Inria; Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Sorbonne Universite; Universite Paris Cite
摘要：In the context of correlated Multiple tests, we aim to nonasymptotically control the family-wise error rate (FWER) using resampling-type procedures. We observe repeated realizations of a Gaussian random vector in possibly high dimension and with an unknown covariance matrix, and consider the one- and two-sided multiple testing problem for the mean values of its coordinates. We address this problem by using the confidence regions developed in the companion paper [Ann. Statist. (2009), to appear...
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作者：Wang, Jane-Ling; Xue, Liugen; Zhu, Lixing; Chong, Yun Sam
作者单位：University of California System; University of California Davis; Beijing University of Technology; Hong Kong Baptist University
摘要：In this paper, we study the estimation for a partial-linear single-index model. A two-stage estimation procedure is proposed to estimate the link function for the single index and the parameters in the single index, as well as the parameters in the linear component of the model. Asymptotic normality is established for both parametric components. For the index, a constrained estimating equation leads to an asymptotically more efficient estimator than existing estimators in the sense that it is ...
