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作者：Bull, Adam D.
作者单位：University of Cambridge
摘要：In quantitative finance, we often model asset prices as a noisy Ito semimartingale. As this model is not identifiable, approximating by a time-changed Levy process can be useful for generative modelling. We give a new estimate of the normalised volatility or time change in this model, which obtains minimax convergence rates, and is unaffected by infinite-variation jumps. In the semimartingale model, our estimate remains accurate for the normalised volatility, obtaining convergence rates as goo...
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作者：Zhou, Zhou
作者单位：University of Toronto
摘要：We investigate the behavior of Fourier transforms for a wide class of nonstationary nonlinear processes. Asymptotic central and noncentral limit theorems are established for a class of nondegenerate and degenerate weighted V-statistics through the angle of Fourier analysis. The established theory for V-statistics provides a unified treatment for many important time and spectral domain problems in the analysis of nonstationary time series, ranging from nonparametric estimation to the inference ...
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作者：Bibinger, Markus; Hautsch, Nikolaus; Malec, Peter; Reiss, Markus
作者单位：Humboldt University of Berlin; University of Vienna; Humboldt University of Berlin
摘要：An efficient estimator is constructed for the quadratic covariation or integrated co-volatility matrix of a multivariate continuous martingale based on noisy and nonsynchronous observations under high-frequency asymptotics. Our approach relies on an asymptotically equivalent continuous-time observation model where a local generalised method of moments in the spectral domain turns out to be optimal. Asymptotic semi-parametric efficiency is established in the Cramer-Rao sense. Main findings are ...
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作者：Arias-Castro, Ery; Verzelen, Nicolas
作者单位：University of California System; University of California San Diego; INRAE
摘要：We formalize the problem of detecting a community in a network into testing whether in a given (random) graph there is a subgraph that is unusually dense. Specifically, we observe an undirected and unweighted graph on N nodes. Under the null hypothesis, the graph is a realization of an Erdos-Renyi graph with probability p(0). Under the (composite) alternative, there is an unknown subgraph of n nodes where the probability of connection is P-1 > p(0). We derive a detection lower bound for detect...
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作者：Guo, Wenge; He, Li; Sarkar, Sanat K.
作者单位：New Jersey Institute of Technology; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：The probability of false discovery proportion (FDP) exceeding gamma is an element of [0, 1), defined as gamma-FDP, has received much attention as a measure of false discoveries in multiple testing. Although this measure has received acceptance due to its relevance under dependency, not much progress has been made yet advancing its theory under such dependency in a nonasymptotic setting, which motivates our research in this article. We provide a larger class of procedures containing the stepup ...
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作者：Zhou, Shuheng
作者单位：University of Michigan System; University of Michigan
摘要：Undirected graphs can be used to describe matrix variate distributions. In this paper, we develop new methods for estimating the graphical structures and underlying parameters, namely, the row and column covariance and inverse covariance matrices from the matrix variate data. Under sparsity conditions, we show that one is able to recover the graphs and covariance matrices with a single random matrix from the matrix variate normal distribution. Our method extends, with suitable adaptation, to t...
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作者：Jiang, Ci-Ren; Yu, Wei; Wang, Jane-Ling
作者单位：Academia Sinica - Taiwan; Roche Holding; Roche Holding USA; Genentech; University of California System; University of California Davis
摘要：Sliced inverse regression (Duan and Li [Ann. Statist. 19 (1991) 505-530], Li [J. Amer. Statist. Assoc. 86 (1991) 316-342]) is an appealing dimension reduction method for regression models with multivariate covariates. It has been extended by Ferro and Yao [Statistics 37 (2003) 475-488, Statist. Sinica 15 (2005) 665-683] and Hsing and Ren [Ann. Statist. 37 (2009) 726-755] to functional covariates where the whole trajectories of random functional covariates are completely observed. The focus of ...
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作者：Jirak, Moritz; Meister, Alexander; Reiss, Markus
作者单位：Humboldt University of Berlin; University of Rostock
摘要：We consider the model of nonregular nonparametric regression where smoothness constraints are imposed on the regression function f and the regression errors are assumed to decay with some sharpness level at their endpoints. The aim of this paper is to construct an adaptive estimator for the regression function f. In contrast to the standard model where local averaging is fruitful, the nonregular conditions require a substantial different treatment based on local extreme values. We study this m...
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作者：Genovese, Christopher R.; Perone-Pacifico, Marco; Verdinelli, Isabella; Wasserman, Larry
作者单位：Carnegie Mellon University; Sapienza University Rome
摘要：We study the problem of estimating the ridges of a density function. Ridge estimation is an extension of mode finding and is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data. We show that, under mild regularity conditions, the ridges of the kernel density estimator consistently estimate the ridges of the true density. When the data are noisy measurements of a manifold, we show that the ridges are close and topologically simil...
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作者：Wang, Li; Xue, Lan; Qu, Annie; Liang, Hua
作者单位：University System of Georgia; University of Georgia; Oregon State University; University of Illinois System; University of Illinois Urbana-Champaign; George Washington University
摘要：We propose generalized additive partial linear models for complex data which allow one to capture nonlinear patterns of some covariates, in the presence of linear components. The proposed method improves estimation efficiency and increases statistical power for correlated data through incorporating the correlation information. A unique feature of the proposed method is its capability of handling model selection in cases where it is difficult to specify the likelihood function. We derive the qu...
