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作者：Heiny, Johannes; Yao, Jianfeng
作者单位：Ruhr University Bochum; The Chinese University of Hong Kong, Shenzhen
摘要：Consider a p-dimensional population x is an element of R-p with i.i.d. coordinates that are regularly varying with index alpha is an element of(0, 2). Since the variance of x is infinite, the diagonal elements of the sample covariance matrix S-n = n(-1) Sigma(n)(i=1) x(i)x(i)' based on a sample x(1), . . . , x(n) from the population tend to infinity as n increases and it is of interest to use instead the sample correlation matrix R-n = {diag(S-n)}S--1/2(n){diag(S-n)}(-1/2). This paper finds th...
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作者：Chernozhuokov, Victor; Chetverikov, Denis; Kato, Kengo; Koike, Yuta
作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); University of California System; University of California Los Angeles; Cornell University; University of Tokyo; University of Tokyo
摘要：This paper deals with the Gaussian and bootstrap approximations to the distribution of the max statistic in high dimensions. This statistic takes the form of the maximum over components of the sum of independent random vectors and its distribution plays a key role in many high-dimensional estimation and testing problems. Using a novel iterative randomized Lindeberg method, the paper derives new bounds for the distributional approximation errors. These new bounds substantially improve upon exis...
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作者：Velasco, Carlos
作者单位：Universidad Carlos III de Madrid
摘要：We propose new estimation methods for time series models, possibly noncausal and/or noninvertible, using serial dependence information from the characteristic function of model residuals. This allows to impose the i.i.d. or martingale difference assumptions on the model errors to identify the unknown location of the roots of the lag polynomials for ARMA models without resorting to higher order moments or distributional assumptions. We consider generalized spectral density and cumulative distri...
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作者：Berthet, Philippe; Einmahl, John H. J.
作者单位：Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Universite Federale Toulouse Midi-Pyrenees (ComUE); Institut National des Sciences Appliquees de Toulouse; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Centre National de la Recherche Scientifique (CNRS); Tilburg University
摘要：Given n independent random vectors with common density f on R-d, we study the weak convergence of three empirical-measure based estimators of the convex lambda-level set L-lambda of f, namely the excess mass set, the minimum volume set and the maximum probability set, all selected from a class of convex sets A that contains L-lambda. Since these set-valued estimators approach L-lambda, even the formulation of their weak convergence is nonstandard. We identify the joint limiting distribution of...
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作者：Wang, Runmin; Zhu, Changbo; Volgushev, Stanislav; Shao, Xiaofeng
作者单位：Southern Methodist University; University of California System; University of California Davis; University of Toronto; University of Illinois System; University of Illinois Urbana-Champaign
摘要：This article considers change-point testing and estimation for a sequence of high-dimensional data. In the case of testing for a mean shift for high-dimensional independent data, we propose a new test which is based on U-statistic in Chen and Qin (Ann. Statist. 38 (2010) 808-835) and utilizes the self-normalization principle (Shao J. R. Stat. Soc. Ser. B. Stat. Methodol. 72 (2010) 343-366; Shao and Zhang J. Amer. Statist. Assoc. 105 (2010) 1228-1240). Our test targets dense alternatives in the...
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作者：Chen, Guanzhou; Tang, Boxin
作者单位：Simon Fraser University
摘要：Space-filling designs based on orthogonal arrays are attractive for computer experiments for they can be easily generated with desirable low-dimensional stratification properties. Nonetheless, it is not very clear how they behave and how to construct good such designs under other space-filling criteria. In this paper, we justify orthogonal array-based designs under a broad class of space-filling criteria, which include commonly used distance-, orthogonality- and discrepancy-based measures. To ...
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作者：Rytgaard, Helene C.; Gerds, Thomas A.; van der Laan, Mark J.
作者单位：University of Copenhagen; University of California System; University of California Berkeley; University of California System; University of California Berkeley
摘要：This paper generalizes the targeted minimum loss-based estimation (TMLE) framework to allow for estimating the effects of time-varying interventions in settings where both interventions, covariates, and outcome can happen at subject-specific time-points on an arbitrarily fine time-scale. TMLE is a general template for constructing asymptotically linear substitution estimators for smooth low-dimensional parameters in infinite-dimensional models. Existing longitudinal TMLE methods are developed ...
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作者：Koskela, Jere; Jenkins, Paul A.; Johansen, Adam M.; Spano, Dario
作者单位：University of Warwick
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作者：Niles-Weed, Jonathan; Berthet, Quentin
作者单位：New York University; Alphabet Inc.; Google Incorporated
摘要：We study nonparametric density estimation problems where error is measured in the Wasserstein distance, a metric on probability distributions popular in many areas of statistics and machine learning. We give the first minimax-optimal rates for this problem for general Wasserstein distances for two classes of densities: smooth probability densities on [0, 1](d) bounded away from 0, and sub-Gaussian densities lying in the Holder class C-s, s is an element of (0, 1). Unlike classical nonparametri...
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作者：Albert, Melisande; Laurent, Beatrice; Marrel, Amandine; Meynaoui, Anouar
作者单位：Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Universite Federale Toulouse Midi-Pyrenees (ComUE); Institut National des Sciences Appliquees de Toulouse; Universite Federale Toulouse Midi-Pyrenees (ComUE); Universite de Toulouse; Institut National des Sciences Appliquees de Toulouse; Centre National de la Recherche Scientifique (CNRS); CEA; Centre National de la Recherche Scientifique (CNRS)
摘要：The Hilbert-Schmidt Independence Criterion (HSIC) is a dependence measure based on reproducing kernel Hilbert spaces that is widely used to test independence between two random vectors. Remains the delicate choice of the kernel. In this work, we develop a new HSIC-based aggregated procedure which avoids such a kernel choice, and provide theoretical guarantees for this procedure. To achieve this, on the one hand, we introduce non-asymptotic single tests based on Gaussian kernels with a given ba...
