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作者：Shephard, Neil; Yang, Justin J.
作者单位：Harvard University; Harvard University
摘要：This article proposes a novel model of financial prices where (i) prices are discrete; (ii) prices change in continuous time; (iii) a high proportion of price changes are reversed in a fraction of a second. Our model is analytically tractable and directly formulated in terms of the calendar time and price impact curve. The resulting cadlag price process is a piecewise constant semimartingale with finite activity, finite variation, and no Brownian motion component. We use moment-based estimatio...
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作者：Wang, Xiao; Zhu, Hongtu
作者单位：Purdue University System; Purdue University; University of North Carolina; University of North Carolina Chapel Hill
摘要：The use of imaging markers to predict clinical outcomes can have a great impact in public health. The aim of this article is to develop a class of generalized scalar-on-image regression models via total variation (GSIRM-TV), in the sense of generalized linear models, for scalar response and imaging predictor with the presence of scalar covariates. A key novelty of GSIRM-TV is that it is assumed that the slope function (or image) of GSIRM-TV belongs to the space of bounded total variation to ex...
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作者：Cai, Tianxi; Cai, T. Tony; Zhang, Anru
作者单位：University of Pennsylvania
摘要：Matrix completion has attracted significant recent attention in many fields including statistics, applied mathematics, and electrical engineering. Current literature on matrix completion focuses primarily on-independent sampling models under which the individual observed entries are sampled independently. Motivated by applications in genomic data integration, we propose a new framework of structured matrix completion (SMC) to treat structured rnissingness by design. Specifically, our proposed ...
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作者：Chen, Mengjie; Ren, Zhao; Zhao, Hongyu; Zhou, Harrison
作者单位：University of North Carolina; University of North Carolina Chapel Hill; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Yale University; Yale University
摘要：We propose an asymptotically normal and efficient procedure to estimate every finite subgraph for covariate-adjusted Gaussian graphical model. As a consequence, a confidence interval as well as p-value can be obtained for each edge. The procedure is tuning-free and enjoys easy implementation and efficient computation through parallel estimation on subgraphs or edges. We apply the asymptotic normality result to perform support recovery through edge-wise adaptive thresholding. This support recov...
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作者：Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin
作者单位：Princeton University; Columbia University; University of North Carolina; University of North Carolina Charlotte; University of Southern California
摘要：We propose a high-dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensio...
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作者：Kneib, Thomas
作者单位：University of Gottingen
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作者：Chen, Yang; Shen, Kuang; Shan, Shu-Ou; Kou, S. C.
作者单位：Harvard University; Massachusetts Institute of Technology (MIT); Whitehead Institute; California Institute of Technology
摘要：To maintain proper cellular functions, over 50% of proteins encoded in the genome need to be transported to cellular membranes. The molecular mechanism behind such a process, often referred to as protein targeting, is not well understood. Single-molecule experiments are designed to unveil the detailed mechanisms and reveal the functions of different molecular machineries involved in the process. The experimental data consist of hundreds of stochastic time traces from the fluorescence recording...
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作者：Feng, Long; Zou, Changliang; Wang, Zhaojun
作者单位：Nankai University; Nankai University
摘要：This article concerns tests for the two-sample location problem when data dimension is larger than the sample size. Existing multivariate-sign-based procedures are not robust against high dimensionality, producing tests with Type I error rates far away from nominal levels. This is mainly due to the biases from estimating location parameters. We propose,a novel test to overcome this issue by using the leave-one-out idea. The proposed test statistic is scalar-invariant and thus is particularly u...
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作者：Fogarty, Colin B.; Mikkelsen, Mark E.; Gaieski, David F.; Small, Dylan S.
作者单位：University of Pennsylvania
摘要：Motivated by an observational study of the effect of hospital ward versus intensive care unit admission on severe sepsis mortality, we develop methods to address two common problems in observational studies: (1) when there is a lack of covariate overlap between the treated and control groups, how to define an interpretable study population wherein inference can be conducted without extrapolating with respect to important variables; and (2) how to use randomization inference to form confidence ...
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作者：Du, Chao; Kao, Chu-Lan Michael; Kou, S. C.
作者单位：University of Virginia; National Central University; Harvard University
摘要：This article studies the estimation of a stepwise signal. To determine the number and locations of change-points of the stepwise signal, we formulate a maximum marginal likelihood estimator, which can be computed with a quadratic cost using dynamic programming. We carry out an extensive investigation on the choice of the prior distribution and study the asymptotic properties of the maximum marginal likelihood estimator. We propose to treat each possible set of change-points equally and adopt a...
