2013

最新文章

• Latent Supervised Learning AI翻译
  作者：Wei, Susan; Kosorok, Michael R.
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
  摘要：This article introduces a new machine learning task, called latent supervised learning, where the goal is to learn a binary classifier from continuous training labels that serve as surrogates for the unobserved class labels. We investigate a specific model where the surrogate variable arises from a two-component Gaussian mixture with unknown means and variances, and the component membership is determined by a hyperplane in the covariate space. The estimation of the separating hyperplane and th...
• Effectively Selecting a Target Population for a Future Comparative Study AI翻译
  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...
• On Sampling Strategies in Bayesian Variable Selection Problems With Large Model Spaces AI翻译
  作者：Garcia-Donato, G.; Martinez-Beneito, M. A.
  作者单位：Universidad de Castilla-La Mancha; CIBER - Centro de Investigacion Biomedica en Red; CIBERESP
  摘要：One important aspect of Bayesian model selection is how to deal with huge model spaces, since the exhaustive enumeration of all the models entertained is not feasible and inferences have to be based on the very small proportion of models visited. This is the case for the variable selection problem with a moderately large number of possible explanatory variables considered in this article. We review some of the strategies proposed in the literature, from a theoretical point of view using argume...
• A Marginal Approach to Reduced-Rank Penalized Spline Smoothing With Application to Multilevel Functional Data AI翻译
  作者：Chen, Huaihou; Wang, Yuanjia; Paik, Myunghee Cho; Choi, H. Alex
  作者单位：New York University; Columbia University; Seoul National University (SNU); University of Texas System; University of Texas Health Science Center Houston
  摘要：Multilevel functional data are collected in many biomedical studies. For example, in a study of the effect of Nimodipine on patients with subarachnoid hemorrhage (SAH), patients underwent multiple 4-hr treatment cycles. Within each treatment cycle, subjects' vital signs were reported every 10 min. These data have a natural multilevel structure with treatment cycles nested within subjects and measurements nested within cycles. Most literature on nonparametric analysis of suchmultilevel function...
• Estimation of Censored Quantile Regression for Panel Data With Fixed Effects AI翻译
  作者：Galvao, Antonio F.; Lamarche, Carlos; Lima, Luiz Renato
  作者单位：University of Iowa; University of Kentucky; University of Tennessee System; University of Tennessee Knoxville; Universidade Federal da Paraiba
  摘要：This article investigates estimation of censored quantile regression (QR) models with fixed effects. Standard available methods are not appropriate for estimation of a censored QR model with a large number of parameters or with covariates correlated with unobserved individual heterogeneity. Motivated by these limitations, the article proposes estimators that are obtained by applying fixed effects QR to subsets of observations selected either parametrically or nonparametrically. We derive the l...
• Auxiliary Marker-Assisted Classification in the Absence of Class Identifiers AI翻译
  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...
• Clustering High-Dimensional Time Series Based on Parallelism AI翻译
  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...
• Estimating Latent Processes on a Network From Indirect Measurements AI翻译
  作者：Airoldi, Edoardo M.; Blocker, Alexander W.
  作者单位：Harvard University; Harvard University
  摘要：In a communication network, point-to-point traffic volumes over time are critical for designing protocols that route information efficiently and for maintaining security, whether at the scale of an Internet service provider or within a corporation. While technically feasible, the direct measurement of point-to-point traffic imposes a heavy burden on network performance and is typically not implemented. Instead, indirect aggregate traffic volumes are routinely collected. We consider the problem...
• Misspecification Testing in a Class of Conditional Distributional Models AI翻译
  作者：Rothe, Christoph; Wied, Dominik
  作者单位：Columbia University; Dortmund University of Technology
  摘要：We propose a specification test for a wide range of parametric models for the conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data and a restricted estimate that imposes the structure implied by the model. The procedure is straightforward to implement, is consistent against fixed alternatives, has nontrivial power against local dev...
• Validation of Visual Statistical Inference, Applied to Linear Models AI翻译
  作者：Majumder, Mahbubul; Hofmann, Heike; Cook, Dianne
  作者单位：Iowa State University
  摘要：Statistical graphics play a crucial role in exploratory data analysis, model checking, and diagnosis. The lineup protocol enables statistical significance testing of visual findings, bridging the gulf between exploratory and inferential statistics. In this article, inferential methods for statistical graphics are developed further by refining the terminology of visual inference and framing the lineup protocol in a context that allows direct comparison with conventional tests in scenarios when ...