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作者：Hornstein, Michael; Fan, Roger; Shedden, Kerby; Zhou, Shuheng
作者单位：University of Michigan System; University of Michigan; University of California System; University of California Riverside
摘要：It has been proposed that complex populations, such as those that arise in genomics studies, may exhibit dependencies among observations as well as among variables. This gives rise to the challenging problem of analyzing unreplicated high-dimensional data with unknown mean and dependence structures. Matrix-variate approaches that impose various forms of (inverse) covariance sparsity allow flexible dependence structures to be estimated, but cannot directly be applied when the mean and covarianc...
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作者：Tibshirani, Ryan J.; Rosset, Saharon
作者单位：Carnegie Mellon University; Carnegie Mellon University; Tel Aviv University
摘要：Nearly all estimators in statistical prediction come with an associated tuning parameter, in one way or another. Common practice, given data, is to choose the tuning parameter value that minimizes a constructed estimate of the prediction error of the estimator; we focus on Stein's unbiased risk estimator, or SURE, which forms an unbiased estimate of the prediction error by augmenting the observed training error with an estimate of the degrees of freedom of the estimator. Parameter tuning via S...
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作者：Young, Jessica G.; Logan, Roger W.; Robins, James M.; Hernan, Miguel A.
作者单位：Harvard University; Harvard Medical School; Harvard Pilgrim Health Care; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Massachusetts Institute of Technology (MIT)
摘要：Researchers are often interested in using observational data to estimate the effect on a health outcome of maintaining a continuous treatment within a prespecified range over time, for example, always exercise at least 30 minutes per day. There may be many precise interventions that could achieve this range. In this article, we consider representative interventions. These are special cases of random dynamic interventions: interventions under which treatment at each time is assigned according t...
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作者：Cao, Yuanpei; Lin, Wei; Li, Hongzhe
作者单位：University of Pennsylvania; Peking University; Peking University
摘要：High-dimensional compositional data arise naturally in many applications such as metagenomic data analysis. The observed data lie in a high-dimensional simplex, and conventional statistical methods often fail to produce sensible results due to the unit-sum constraint. In this article, we address the problem of covariance estimation for high-dimensional compositional data and introduce a composition-adjusted thresholding (COAT) method under the assumption that the basis covariance matrix is spa...
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作者：Mak, Simon; Wu, C. F. Jeff
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：This article introduces a novel method for selecting main effects and a set of reparameterized effects called conditional main effects (CMEs), which capture the conditional effect of a factor at a fixed level of another factor. CMEs represent interpretable, domain-specific phenomena for a wide range of applications in engineering, social sciences, and genomics. The key challenge is in incorporating the implicit grouped structure of CMEs within the variable selection procedure itself. We propos...
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作者：Zhang, Rongmao; Robinson, Peter; Yao, Qiwei
作者单位：Zhejiang University; Zhejiang University; University of London; London School Economics & Political Science; University of London; London School Economics & Political Science; Peking University
摘要：We propose a new and easy-to-use method for identifying cointegrated components of nonstationary time series, consisting of an eigenanalysis for a certain nonnegative definite matrix. Our setting is model-free, and we allow the integer-valued integration orders of the observable series to be unknown, and to possibly differ. Consistency of estimates of the cointegration space and cointegration rank is established both when the dimension of the observable time series is fixed as sample size incr...
