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作者：Percival, Daniel
作者单位：Carnegie Mellon University
摘要：This article introduces a method for aggregating many least-squares estimators so that the resulting estimate has two properties: sparsity and structure. That is, only a few candidate covariates are used in the resulting model, and the selected covariates follow some structure over the candidate covariates that is assumed to be known a priori. Although sparsity is well studied in many settings, including aggregation, structured sparse methods are still emerging. We demonstrate a general framew...
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作者：Fisher, Thomas J.; Gallagher, Colin M.
作者单位：University of Missouri System; University of Missouri Kansas City; Clemson University
摘要：We exploit ideas from high-dimensional data analysis to derive new portmanteau tests that are based on the trace of the square of the mth order autocorrelation matrix. The resulting statistics are weighted sums of the squares of the sample autocorrelation coefficients that, unlike many other tests appearing in the literature, are numerically stable even when the number of lags considered is relatively close to the sample size. The statistics behave asymptotically as a linear combination of chi...
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作者：Bhaumik, Dulal K.; Amatya, Anup; Normand, Sharon-Lise T.; Greenhouse, Joel; Kaizar, Eloise; Neelon, Brian; Gibbons, Robert D.
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; New Mexico State University; Harvard University; Harvard Medical School; Carnegie Mellon University; University System of Ohio; Ohio State University; Duke University; University of Chicago; University of Chicago; University of Chicago
摘要：We examine the use of fixed-effects and random-effects moment-based meta-analytic methods for analysis of binary adverse-event data. Special attention is paid to the case of rare adverse events that are commonly encountered in routine practice. We study estimation of model parameters and between-study heterogeneity. In addition, we examine traditional approaches to hypothesis testing of the average treatment effect and detection of the heterogeneity of treatment effect across studies. We deriv...
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作者：Kang, Hakmook; Ombao, Hernando; Linkletter, Crystal; Long, Nicole; Badre, David
作者单位：Vanderbilt University; University of California System; University of California Irvine; Brown University; Brown University
摘要：The goal of this article is to model cognitive control related activation among predefined regions of interest (ROIs) of the human brain while properly adjusting for the underlying spatio-temporal correlations. Standard approaches to fMRI analysis do not simultaneously take into account both the spatial and temporal correlations that are prevalent in fMRI data. This is primarily due to the computational complexity of estimating the spatio-temporal covariance matrix. More specifically, they do ...
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作者：Sun, Wenguang; McLain, Alexander C.
作者单位：University of Southern California; National Institutes of Health (NIH) - USA; NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
摘要：In large-scale studies, the true effect sizes often range continuously from zero to small to large, and are observed with heteroscedastic errors. In practical situations where the failure to reject small deviations from the null is inconsequential, specifying an indifference region (or forming composite null hypotheses) can greatly reduce the number of unimportant discoveries in multiple testing. The heteroscedasticity issue poses new challenges for multiple testing with composite nulls. In pa...
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作者：Luati, Alessandra; Proietti, Tommaso; Reale, Marco
作者单位：University of Bologna; University of Sydney; University of Rome Tor Vergata; University of Canterbury
摘要：The variance profile is defined as the power mean of the spectral density function of a stationary stochastic process. It is a continuous and nondecreasing function of the power parameter, p, which returns the minimum of the spectrum (p -> infinity), the interpolation error variance (harmonic mean, p = -1), the prediction error variance (geometric mean, p = 0), the unconditional variance (arithmetic mean, p = 1), and the maximum of the spectrum (p -> infinity). The variance profile provides a ...
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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 consider the problem of estimating filamentary structure from d-dimensional point process data. We make some connections with computational geometry and develop nonparametric methods for estimating the filaments. We show that, under weak conditions, the filaments have a simple geometric representation as the medial axis of the data distribution's support. Our methods convert an estimator of the support's boundary into an estimator of the filaments. We also find the rates of convergence of o...
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作者：Huang, Mian; Yao, Weixin
作者单位：Shanghai University of Finance & Economics; Kansas State University
摘要：In this article, we study a class of semiparametric mixtures of regression models, in which the regression functions are linear functions of the predictors, but the mixing proportions are smoothing functions of a covariate. We propose a one-step backfitting estimation procedure to achieve the optimal convergence rates for both regression parameters and the nonparametric functions of mixing proportions. We derive the asymptotic bias and variance of the one-step estimate, and further establish i...
