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作者：Yuan, Ming; Cai, T. Tony
作者单位：University System of Georgia; Georgia Institute of Technology; University of Pennsylvania
摘要：We study in this paper a smoothness regularization method for functional linear regression and provide a unified treatment for both the prediction and estimation problems. By developing a tool on simultaneous diagonalization of two positive definite kernels, we obtain shaper results on the minimax rates of convergence and show that smoothness regularized estimators achieve the optimal rates of convergence for both prediction and estimation under conditions weaker than those for the functional ...
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作者：Du, Pang; Ma, Shuangge; Liang, Hua
作者单位：Virginia Polytechnic Institute & State University; Yale University; University of Rochester
摘要：We study the Cox models with semiparametric relative risk, which can be partially linear with one nonparametric component, or multiple additive or nonadditive nonparametric components. A penalized partial likelihood procedure is proposed to simultaneously estimate the parameters and select variables for both the parametric and the nonparametric parts. Two penalties are applied sequentially. The first penalty, governing the smoothness of the multivariate nonlinear covariate effect function, pro...
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作者：Norets, Andriy
作者单位：Princeton University
摘要：This paper shows that large nonparametric classes of conditional multivariate densities can be approximated in the Kullback-Leibler distance by different specifications of finite mixtures of normal regressions in which normal means and variances and mixing probabilities can depend on variables in the conditioning set (covariates). These models are a special case of models known as mixtures of experts in statistics and computer science literature. Flexible specifications include models in which...
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作者：Chen, Song Xi; Qin, Ying-Li
作者单位：Iowa State University; Peking University
摘要：We propose a two-sample test for the means of high-dimensional data when the data dimension is much larger than the sample size. Hotelling's classical T(2) test does not work for this large p, small n situation. The proposed test does not require explicit conditions in the relationship between the data dimension and sample size. This offers much flexibility in analyzing high-dimensional data. An application of the proposed test is in testing significance for sets of genes which we demonstrate ...
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作者：Egloff, Daniel; Leippold, Markus
作者单位：University of Zurich
摘要：We introduce new quantile estimators with adaptive importance sampling. The adaptive estimators are based on weighted samples that are neither independent nor identically distributed. Using a new law of iterated logarithm for martingales, we prove the convergence of the adaptive quantile estimators for general distributions with nonunique quantiles thereby extending the work of Feldman and Tucker [Ann. Math. Statist. 37 (1996) 451-457]. We illustrate the algorithm with an example from credit p...
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作者：Serfling, Robert; Zuo, Yijun
作者单位：University of Texas System; University of Texas Dallas; Michigan State University
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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：Drees, Holger; Rootzen, Holger
作者单位：University of Hamburg; Chalmers University of Technology; University of Gothenburg
摘要：Let (X-n, i) 1 <= i <= n,m is an element of N be a triangular array of row-wise stationary R-d-valued random variables. We use a blocks method to define clusters of extreme values: the rows of (X-n, i) are divided into m(n) blocks (Y-n, j), and if a block contains at least one extreme value, the block is considered to contain a cluster. The cluster starts at the first extreme value in the block and ends at the last one. The main results are uniform central limit theorems for empirical processe...
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作者：Zhou, Zhou
作者单位：University of Toronto
摘要：The paper considers nonparametric specification tests of quantile curves for a general class of nonstationary processes. Using Bahadur representation and Gaussian approximation results for nonstationary time series, simultaneous confidence bands and integrated squared difference tests are proposed to test various parametric forms of the quantile curves with asymptotically correct type I error rates. A wild bootstrap procedure is implemented to alleviate the problem of slow convergence of the a...
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作者：Hormann, Siegfried; Kokoszka, Piotr
作者单位：Universite Libre de Bruxelles; Utah System of Higher Education; Utah State University
摘要：Functional data often arise from measurements on tine time grids and are obtained by separating an almost continuous time record into natural consecutive intervals, or example, days. The functions thus obtained form a functional time series, and the central issue in the analysis of such data consists in taking into account the temporal dependence of these functional observations. Examples include daily curves of financial transaction data and daily patterns of geophysical and environmental dat...
