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作者：Shen, Xiaotong; Pan, Wei; Zhu, Yunzhang
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
摘要：In high-dimensional data analysis, feature selection becomes one effective means for dimension reduction, which proceeds with parameter estimation. Concerning accuracy of selection and estimation, we study nonconvex constrained and regularized likelihoods in the presence of nuisance parameters. Theoretically, we show that constrained L-0 likelihood and its computational surrogate are optimal in that they achieve feature selection consistency and sharp parameter estimation, under one necessary ...
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作者：Chen, Lisha; Huang, Jianhua Z.
作者单位：Yale University; Texas A&M University System; Texas A&M University College Station
摘要：The reduced-rank regression is an effective method in predicting multiple response variables from the same set of predictor variables. It reduces the dumber of model parameters and takes advantage of interrelations between. the response variables and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as ...
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作者：Cai, T. Tony; Yuan, Ming
作者单位：University of Pennsylvania; University System of Georgia; Georgia Institute of Technology
摘要：This article considers minimax and adaptive prediction with functional predictors in the framework of functional linear model and reproducing kernel Hilbert space. Minimax rate of convergence for the excess prediction risk is established. It is shown that the optimal rate is determined jointly by the reproducing kernel and the covariance kernel. In particular, the alignment of these two kernels can significantly affect the difficulty of the prediction problem. In contrast, the existing literat...
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作者：Dette, Holger; Trampisch, Matthias
作者单位：Ruhr University Bochum
摘要：Despite their importance, optimal designs for quantile regression models have not been developed so far. In this article, we investigate the D-optimal design problem for nonlinear quantile regression analysis. We provide a necessary condition to check the optimality of a given design and use it to determine bounds for the number of support points of locally D-optimal designs. The results are illustrated, determining locally, Bayesian and standardized maximin D-optimal designs for quantile regr...
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作者：Hu, Jianhua; He, Xuming
作者单位：University of Texas System; UTMD Anderson Cancer Center; University of Michigan System; University of Michigan
摘要：The exon tiling array offers a high throughput technology to search for aberrant splicing in biomedical research, but few methods of analysis for splicing detection have been tested both statistically and empirically. Noisy measurements on nonresponsive probe selection regions and outlying intensities at some of the samples tend to distort model-based assessments. We propose a robust analysis of variance approach that incorporates an informative model on probe measurability and uses median reg...
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作者：Panagiotelis, Anastasios; Czado, Claudia; Joe, Harry
作者单位：Monash University; Technical University of Munich; University of British Columbia
摘要：Multivariate discrete response data can be found in diverse fields, including econometrics, finance, biometrics, and psychometrics. Our contribution, through this study, is to introduce a new class of models for multivariate discrete data based on pair copula constructions (PCCs) that has two major advantages. First, by deriving the conditions under which any multivariate discrete distribution can be decomposed as a PCC, we show that discrete PCCs attain highly flexible dependence structures. ...
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作者：Zubizarreta, Jose R.; Neuman, Mark; Silber, Jeffrey H.; Rosenbaum, Paul R.
作者单位：University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia
摘要：In a randomized trial, subjects are assigned to treatment or control by the flip of a fair coin. In many nonrandomized or observational studies, subjects find their way to treatment or control in two steps, either or both of which may lead to biased comparisons. By a vague process, perhaps affected by proximity or sociodemographic issues, subjects find their way to institutions that provide treatment. Once at such an institution, a second process, perhaps thoughtful and deliberate, assigns ind...
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作者：Nordman, Daniel J.; Lahiri, Soumendra N.
作者单位：Iowa State University; Texas A&M University System; Texas A&M University College Station
摘要：This article examines block bootstrap methods in linear regression models with weakly dependent error variables and nonstochastic regressors. Contrary to intuition, the tapered block bootstrap (TB B) with a smooth taper not only loses its superior bias properties but may also fail to be consistent in the regression problem. A similar problem, albeit at a smaller scale, is shown to exist for the moving and the circular block bootstrap (MBB and CBB, respectively). As a remedy, an additional bloc...
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作者：Hatfield, Laura A.; Boye, Mark E.; Hackshaw, Michelle D.; Carlin, Bradley P.
作者单位：Harvard University; Harvard Medical School; Eli Lilly; Eli Lilly; University of Minnesota System; University of Minnesota Twin Cities
摘要：Regulatory approval of new therapies often depends on demonstrating prolonged survival. Particularly when these survival benefits are modest, consideration of therapeutic benefits to patient-reported outcomes (PROs) may add value to the traditional biomedical clinical trial endpoints. We extend a popular class of joint models for longitudinal and survival data to accommodate the excessive zeros common in PROs, building hierarchical Bayesian models that combine information from longitudinal PRO...
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作者：Zheng, Shurong; Shi, Ning-Zhong; Zhang, Zhengjun
作者单位：Northeast Normal University - China; Northeast Normal University - China; University of Wisconsin System; University of Wisconsin Madison
摘要：Applicability of Pearson's correlation as a measure of explained variance is by now well understood. One of its limitations is that it does not account for asymmetry in explained variance. Aiming to develop broad applicable correlation measures, we study a pair of generalized measures of correlation (GMC) that deals with asymmetries in explained variances, and linear or nonlinear relations between random variables. We present examples under which the paired measures are identical, and they bec...
