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作者：Jiang, Fei; Ma, Yanyuan; Wang, Yuanjia
作者单位：Harvard University; University of South Carolina System; University of South Carolina Columbia; Columbia University
摘要：We propose a generalized partially linear functional single index risk score model for repeatedly measured outcomes where the index itself is a function of time. We fuse the nonparametric kernel method and regression spline method, and modify the generalized estimating equation to facilitate estimation and inference. We use local smoothing kernel to estimate the unspecified coefficient functions of time, and use B-splines to estimate the unspecified function of the single index component. The ...
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作者：Can, Sami Umut; Einmahl, John H. J.; Khmaladze, Estate V.; Laeven, Roger J. A.
作者单位：University of Amsterdam; Tilburg University; Victoria University Wellington
摘要：Let (X-1, Y-1),..., (X-n, Y-n) be an i.i.d sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution. The asymptotic joint distribution of the standardized component-wise maxima V-i=1(n) X-i and V-i=1(n) Y-i is then characterized by the marginal extreme value indices and the tail copula R. We propose a procedure for constructing asymptotically distribution-free goodness-of-fit tests for the tail copula R. The procedure is based on ...
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作者：Zheng, Wei
作者单位：Purdue University System; Purdue University; Purdue University in Indianapolis
摘要：A systematic study is carried out regarding universally optimal designs under the interference model, previously investigated by Kunert and Martin [Ann. Statist. 28 (2000) 1728-1742] and Kunert and Mersmann [J. Statist. Plann. Inference 141 (2011) 1623-1632]. Parallel results are also provided for the undirectional interference model, where the left and right neighbor effects are equal. It is further shown that the efficiency of any design under the latter model is at least its efficiency unde...
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作者：Giraud, Christophe; Roueff, Francois; Sanchez-Perez, Andres
作者单位：Universite Paris Saclay; IMT - Institut Mines-Telecom; Institut Polytechnique de Paris; Telecom Paris; Centre National de la Recherche Scientifique (CNRS)
摘要：In this work, we study the problem of aggregating a finite number of predictors for nonstationary sub-linear processes. We provide oracle inequalities relying essentially on three ingredients: (1) a uniform bound of the 1 norm of the time varying sub-linear coefficients, (2) a Lipschitz assumption on the predictors and (3) moment conditions on the noise appearing in the linear representation. Two kinds of aggregations are considered giving rise to different moment conditions on the noise and m...
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作者：Scornet, Erwan; Biau, Gerard; Vert, Jean-Philippe
作者单位：Sorbonne Universite; Universite PSL; MINES ParisTech; UNICANCER; Universite PSL; Institut Curie; Universite PSL; UNICANCER; Institut Curie; Institut National de la Sante et de la Recherche Medicale (Inserm)
摘要：Random forests are a learning algorithm proposed by Breiman [Mach. Leant. 45 (2001) 5-32] that combines several randomized decision trees and aggregates their predictions by averaging. Despite its wide usage and outstanding practical performance, little is known about the mathematical properties of the procedure. This disparity between theory and practice originates in the difficulty to simultaneously analyze both the randomization process and the highly data-dependent tree structure. In the p...
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作者：Bao, Zhigang; Lin, Liang-Ching; Pan, Guangming; Zhou, Wang
作者单位：Nanyang Technological University; National Cheng Kung University; National University of Singapore
摘要：Let Q = (Qi,...,Qn) be a random vector drawn from the uniform distribution on the set of all n! permutations of {1,2,...,n}. Let Z = (Z1,...,Zn), where Z(j) is the mean zero variance one random variable obtained by centralizing and normalizing Q(j), j = 1,...,n. Assume that X-i, i = 1,...,p are i.i.d. copies of 1 root p Z and X = Xp,n is the p x n random matrix with X-i as its ith row. Then S-n = XX* is called the p x n Spearman's rank correlation matrix which can be regarded as a high dimensi...
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作者：Basu, Sumanta; Michailidis, George
作者单位：University of Michigan System; University of Michigan
摘要：Many scientific and economic problems involve the analysis of high-dimensional time series datasets. However, theoretical studies in high-dimensional statistics to date rely primarily on the assumption of independent and identically distributed (i.i.d.) samples. In this work, we focus on stable Gaussian processes and investigate the theoretical properties of l(1)-regularized estimates in two important statistical problems in the context of high-dimensional time series: (a) stochastic regressio...
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作者：Shang, Zuofeng; Cheng, Guang
作者单位：Purdue University System; Purdue University
摘要：We propose a roughness regularization approach in making nonparametric inference for generalized functional linear models. In a reproducing kernel Hilbert space framework, we construct asymptotically valid confidence intervals for regression mean, prediction intervals for future response and various statistical procedures for hypothesis testing. In particular, one procedure for testing global behaviors of the slope function is adaptive to the smoothness of the slope function and to the structu...
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作者：Vogt, Michael; Dette, Holger
作者单位：University of Konstanz; Ruhr University Bochum
摘要：In a wide range of applications, the stochastic properties of the observed time series change over time. The changes often occur gradually rather than abruptly: the properties are (approximately) constant for some time and then slowly start to change. In many cases, it is of interest to locate the time point where the properties start to vary. In contrast to the analysis of abrupt changes, methods for detecting smooth or gradual change points are less developed and often require strong paramet...
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作者：Sherlock, Chris; Thiery, Alexandre H.; Roberts, Gareth O.; Rosenthal, Jeffrey S.
作者单位：Lancaster University; National University of Singapore; University of Warwick; University of Toronto
摘要：We examine the behaviour of the pseudo-marginal random walk Metropolis algorithm, where evaluations of the target density for the accept/reject probability are estimated rather than computed precisely. Under relatively general conditions on the target distribution, we obtain limiting formulae for the acceptance rate and for the expected squared jump distance, as the dimension of the target approaches infinity, under the assumption that the noise in the estimate of the log-target is additive an...
