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作者：Meinshausen, Nicolai; Buehlmann, Peter
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：Large-scale data are often characterized by some degree of inhomogeneity as data are either recorded in different time regimes or taken from multiple sources. We look at regression models and the effect of randomly changing coefficients, where the change is either smoothly in time or some other dimension or even without any such structure. Fitting varying-coefficient models or mixture models can be appropriate solutions but are computationally very demanding and often return more information t...
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作者：Szabo, Botond; van der Vaart, A. W.; van Zanten, J. H.
作者单位：Eindhoven University of Technology; Leiden University; Leiden University - Excl LUMC; University of Amsterdam
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作者：Yang, Yun; Tokdar, Surya T.
作者单位：University of California System; University of California Berkeley; Duke University
摘要：Minimax L-2 risks for high-dimensional nonparametric regression are derived under two sparsity assumptions: (1) the true regression surface is a sparse function that depends only on d = O(log n) important predictors among a list of p predictors, with log p = o(n); (2) the true regression surface depends on O(n) predictors but is an additive function where each additive component is sparse but may contain two or more interacting predictors and may have a smoothness level different from other co...
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作者：Lei, Jing; Vu, Vincent Q.
作者单位：Carnegie Mellon University; University System of Ohio; Ohio State University
摘要：The presence of a sparse truth has been a constant assumption in the theoretical analysis of sparse PCA and is often implicit in its methodological development. This naturally raises questions about the properties of sparse PCA methods and how they depend on the assumption of sparsity. Under what conditions can the relevant variables be selected consistently if the truth is assumed to be sparse? What can be said about the results of sparse PCA without assuming a sparse and unique truth? We ans...
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作者：Gao, Chao; Lu, Yu; Zhou, Harrison H.
作者单位：Yale University
摘要：Network analysis is becoming one of the most active research areas in statistics Significant advances have been made recently on developing theories, methodologies and algorithms for analyzing networks. However, there has been little fundamental study on optimal estimation. In this paper, we establish optimal rate of convergence for graphon estimation. For the stochastic block model with k clusters, we show that the optimal rate under the mean squared error is n(-1) log k + k(2)/n(2). The mini...
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作者：Delattre, Sylvain; Roquain, Etienne
作者单位：Sorbonne Universite; Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Sorbonne Universite
摘要：The false discovery proportion (FDP) is a convenient way to account for false positives when a large number m of tests are performed simultaneously. Romano and Wolf [Ann. Statist. 35 (2007) 1378-1408] have proposed a general principle that builds FDP controlling procedures from k-family-wise error rate controlling procedures while incorporating dependencies in an appropriate manner; see Korn et al. [J. Statist. Plann. Inference 124 (2004) 379-398]; Romano and Wolf (2007). However, the theoreti...
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作者：Lepski, Oleg
作者单位：Aix-Marseille Universite
摘要：We address the problem of adaptive minimax estimation in white Gaussian noise models under L-p-loss, 1 <= p <= infinity, on the anisotropic Nikol'skii classes. We present the estimation procedure based on a new data-driven selection scheme from the family of kernel estimators with varying bandwidths. For the proposed estimator we establish so-called L-p-norm oracle inequality and use it for deriving minimax adaptive results. We prove the existence of rate-adaptive estimators and fully characte...
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作者：Chauvet, Guillaume
作者单位：Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI)
摘要：Multistage sampling is commonly used for household surveys when there exists no sampling frame, or when the population is scattered over a wide area. Multistage sampling usually introduces a complex dependence in the selection of the final units, which makes asymptotic results quite difficult to prove. In this work, we consider multistage sampling with simple random without replacement sampling at the first stage, and with an arbitrary sampling design for further stages. We consider coupling m...
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作者：Jirak, Moritz
作者单位：Humboldt University of Berlin
摘要：Consider d dependent change point tests, each based on a CUSUM-statistic. We provide an asymptotic theory that allows us to deal with the maximum over all test statistics as both the sample size n and d tend to infinity. We achieve this either by a consistent bootstrap or an appropriate limit distribution. This allows for the construction of simultaneous confidence bands for dependent change point tests, and explicitly allows us to determine the location of the change both in time and coordina...
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作者：Rousseau, Judith
作者单位：Universite PSL; Universite Paris-Dauphine; Institut Polytechnique de Paris; ENSAE Paris
