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作者：van Zwet, Willem R.
作者单位：Leiden University; Leiden University - Excl LUMC
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作者：Tibshirani, Ryan J.; Taylor, Jonathan
作者单位：Stanford University
摘要：We present a path algorithm for the generalized lasso problem. This problem penalizes the l(1) norm of a matrix D times the coefficient vector, and has a wide range of applications, dictated by the choice of D. Our algorithm is based on solving the dual of the generalized lasso, which greatly facilitates computation of the path. For D = I (the usual lasso), we draw a connection between our approach and the well-known LARS algorithm. For an arbitrary D, we derive an unbiased estimate of the deg...
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作者：Comte, Fabienne; Genon-Catalot, Valentine
作者单位：Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); IMT - Institut Mines-Telecom; Institut Polytechnique de Paris; Telecom SudParis
摘要：In this paper, we study nonparametric estimation of the Levy density for Levy processes, with and without Brownian component. For this, we consider n discrete time observations with step Delta. The asymptotic framework is: n tends to infinity, Delta = Delta(n), tends to zero while n Delta(n) tends to infinity. We use a Fourier approach to construct an adaptive nonparametric estimator of the Levy density and to provide a bound for the global L-2-risk. Estimators of the drift and of the variance...
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作者：Jiang, Ci-Ren; Wang, Jane-Ling
作者单位：University of California System; University of California Berkeley; University of California System; University of California Davis
摘要：A new single-index model that reflects the time-dynamic effects of the single index is proposed for longitudinal and functional response data, possibly measured with errors, for both longitudinal and time-invariant covariates. With appropriate initial estimates of the parametric index, the proposed estimator is shown to be root n-consistent and asymptotically normally distributed. We also address the nonparametric estimation of regression functions and provide estimates with optimal convergenc...
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作者：Lounici, Karim; Nickl, Richard
作者单位：University of Cambridge
摘要：We consider the statistical deconvolution problem where one observes n replications from the model Y = X + epsilon, where X is the unobserved random signal of interest and epsilon is an independent random error with distribution phi. Under weak assumptions on the decay of the Fourier transform of phi, we derive upper bounds for the finite-sample sup-norm risk of wavelet deconvolution density estimators f(n) for the density f of X, where f : R -> R is assumed to be bounded. We then derive lower...
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作者：Meinshausen, Nicolai; Maathuis, Marloes H.; Buehlmann, Peter
作者单位：University of Oxford; Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：Test statistics are often strongly dependent in large-scale multiple testing applications. Most corrections for multiplicity are unduly conservative for correlated test statistics, resulting in a loss of power to detect true positives. We show that the Westfall-Young permutation method has asymptotically optimal power for a broad class of testing problems with a block-dependence and sparsity structure among the tests, when the number of tests tends to infinity.
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作者：Yen, Tso-Jung
作者单位：Academia Sinica - Taiwan
摘要：We develop a method to carry out MAP estimation for a class of Bayesian regression models in which coefficients are assigned with Gaussian-based spike and slab priors. The objective function in the corresponding optimization problem has a Lagrangian form in that regression coefficients are regularized by a mixture of squared l(2) and l(0) norms. A tight approximation to the l(0) norm using majorization minimization techniques is derived, and a coordinate descent algorithm in conjunction with a...
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作者：Zhang, Mingyuan; Joffe, Marshall M.; Small, Dylan S.
作者单位：University of Pennsylvania; University of Pennsylvania
摘要：Most of the work on the structural nested model and g-estimation for causal inference in longitudinal data assumes a discrete-time underlying data generating process. However, in some observational studies, it is more reasonable to assume that the data are generated from a continuous-time process and are only observable at discrete time points. When these circumstances arise, the sequential randomization assumption in the observed discrete-time data, which is essential in justifying discrete-t...
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作者：Aue, Alexander; Lee, Thomas C. M.
作者单位：University of California System; University of California Davis
摘要：Image segmentation is a long-studied and important problem in image processing. Different solutions have been proposed, many of which follow the information theoretic paradigm. While these information theoretic segmentation methods often produce excellent empirical results, their theoretical properties are still largely unknown. The main goal of this paper is to conduct a rigorous theoretical study into the statistical consistency properties of such methods. To be more specific, this paper inv...
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作者：Zheng, Xinghua; Li, Yingying
作者单位：Hong Kong University of Science & Technology
摘要：We consider the estimation of integrated covariance (ICV) matrices of high dimensional diffusion processes based on high frequency observations. We start by studying the most commonly used estimator, the realized covariance (RCV) matrix. We show that in the high dimensional case when the dimension p and the observation frequency n grow in the same rate, the limiting spectral distribution (LSD) of RCV depends on the covolatility process not only through the targeting ICV, but also on how the co...
