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作者：Zhao, Lihui; Tian, Lu; Cai, Tianxi; Claggett, Brian; Wei, L. J.
作者单位：Northwestern University; Stanford University; Harvard University; Harvard University; Harvard Medical School
摘要：When comparing a new treatment with a control in a randomized clinical study, the treatment effect is generally assessed by evaluating a summary measure over a specific study population. The success of the trial heavily depends on the choice of such a population. In this article, we show a systematic, effective way to identify a promising population, for which the new treatment is expected to have a desired benefit, using the data from a current study involving similar comparator treatments. S...
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作者：Wang, Yuanjia; Chen, Huaihou; Zeng, Donglin; Mauro, Christine; Duan, Naihua; Shear, M. Katherine
作者单位：Columbia University; New York University; University of North Carolina; University of North Carolina Chapel Hill; Columbia University; Columbia University; Columbia University
摘要：Constructing classification rules for accurate diagnosis of a disorder is an important goal in medical practice. In many clinical applications, there is no clinically significant anatomical or physiological deviation that exists to identify the gold standard disease status to inform development of classification algorithms. Despite the absence of perfect disease class identifiers, there are usually one or more disease-informative auxiliary markers along with feature variables that comprise kno...
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作者：Zhang, Ting
作者单位：University of Iowa
摘要：This article considers the problem of clustering high-dimensional time series based on trend parallelism. The underlying process is modeled as a nonparametric trend function contaminated by locally stationary errors, a special class of nonstationary processes. For each group where the parallelism holds, I semiparametrically estimate its representative trend function and vertical shifts of group members, and establish their central limit theorems. An information criterion, consisting of in-grou...
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作者：Katenka, Natallia; Levina, Elizaveta; Michailidis, George
作者单位：University of Rhode Island; University of Michigan System; University of Michigan
摘要：This article introduces a framework for tracking multiple targets over time using binary decisions collected by a wireless sensor network, and applies the methodology to two case studies-an experiment involving tracking people and a dataset adapted from a project tracking zebras in Kenya. The tracking approach is based on a penalized maximum likelihood framework, and allows for sensor failures, targets appearing and disappearing over time, and complex intersecting target trajectories. We show ...
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作者：Liu, Rong; Yang, Lijian; Haerdle, Wolfgang K.
作者单位：Soochow University - China; University System of Ohio; University of Toledo; Michigan State University; Humboldt University of Berlin
摘要：The generalized additive model (GAM) is a multivariate nonparametric regression tool for non-Gaussian responses including binary and count data. We propose a spline-backfitted kernel (SBK) estimator for the component functions and the constant, which are oracally efficient under weak dependence. The SBK technique is both computationally expedient and theoretically reliable, thus usable for analyzing high-dimensional time series. Inference can be made on component functions based on asymptotic ...
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作者：Wang, Xueqin; Jiang, Yunlu; Huang, Mian; Zhang, Heping
作者单位：Sun Yat Sen University; Sun Yat Sen University; Sun Yat Sen University; Shanghai University of Finance & Economics; Yale University
摘要：Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this article, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is th...
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作者：Fan, Chunpeng; Fine, Jason P.
作者单位：Sanofi-Aventis; Sanofi USA; University of North Carolina; University of North Carolina Chapel Hill
摘要：The traditional linear transformation model assumes a linear relationship between the transformed response and the covariates. However, in real data, this linear relationship may be violated. We propose a linear transformation model that allows parametric covariate transformations to recover the linearity. Although the proposed generalization may seem rather simple, the inferential issues are quite challenging due to loss of identifiability under the null of no effects of transformed covariate...
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作者：Little, Roderick J.
作者单位：University of Michigan System; University of Michigan
摘要：Ronald Fisher was by all accounts a first-rate mathematician, but he saw himself as a scientist, not a mathematician, and he railed against what George Box called (in his Fisher lecture) mathematistry. Mathematics is the indispensable foundation of statistics, but for me the real excitement and value of our subject lies in its application to other disciplines. We should not view statistics as another branch of mathematics and favor mathematical complexity over clarifying, formulating, and solv...
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作者：Sadinle, Mauricio; Fienberg, Stephen E.
作者单位：Carnegie Mellon University; Carnegie Mellon University; Carnegie Mellon University
摘要：We present a probabilistic method for linking multiple datafiles. This task is not trivial in the absence of unique identifiers for the individuals recorded. This is a common scenario when linking census data to coverage measurement surveys for census coverage evaluation, and in general when multiple record systems need to be integrated for posterior analysis. Our method generalizes the Fellegi-Sunter theory for linking records from two datafiles and its modem implementations. The goal of mult...
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作者：Oh, Dong Hwan; Patton, Andrew J.
作者单位：Duke University
摘要：This article considers the estimation of the parameters of a copula via a simulated method of moments (MM) type approach. This approach is attractive when the likelihood of the copula model is not known in closed form, or when the researcher has a set of dependence measures or other functionals of the copula that are of particular interest. The proposed approach naturally also nests MM and generalized method of moments estimators. Drawing on results for simulation-based estimation and on recen...
