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作者：Li, Fan; Zhang, Nancy R.
作者单位：Duke University; Stanford University
摘要：We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate space is comparable, and often much larger, than the number of subjects in the study. and (2) the covariate space is highly structured, and in some cases it is desirable to incorporate this structural information in to the model building proces...
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作者：Li, Lexin; Li, Bing; Zhu, Li-Xing
作者单位：North Carolina State University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Hong Kong Baptist University
摘要：In many regression applications, the predictors fall naturally into a number of groups or domains, and it is often desirable to establish a domain-specific relation between the predictors and the response. In this article, we consider dimension reduction that incorporates such domain knowledge. The proposed method is based on the derivative of the conditional mean, where the differential operator is constrained to the form of a direct sum. This formulation also accommodates the situations wher...
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作者：Gabrys, Robertas; Horvath, Lajos; Kokoszka, Piotr
作者单位：Utah System of Higher Education; Utah State University; Utah System of Higher Education; University of Utah
摘要：The paper proposes two inferential tests for error correlation in the functional linear model, which complement the available graphical goodness-of-fit checks. To construct them, finite dimensional residuals are computed in two different ways, and then their autocorrelations are suitably defined. From these autocorrelation matrices, two quadratic forms are constructed whose limiting distribution are chi-squared with known numbers of degrees of freedom (different for the two forms). The asympto...
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作者：Li, Bo; Nychka, Douglas W.; Ammann, Caspar M.
作者单位：Purdue University System; Purdue University; National Center Atmospheric Research (NCAR) - USA
摘要：Understanding the dynamics of climate change in its full richness requires the knowledge of long temperature time series. Although long-term, widely distributed temperature observations are not available, there are other forms of data, known as climate proxies, that can have a statistical relationship with temperatures and have been used to infer temperatures in the past before direct measurements. We propose a Bayesian hierarchical model to reconstruct past temperatures that integrates inform...
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作者：Gneiting, Tilmann; Kleiber, William; Schlather, Martin
作者单位：Ruprecht Karls University Heidelberg; University of Washington; University of Washington Seattle; University of Gottingen
摘要：We introduce a flexible parametric family of matrix-valued covariance functions for multivariate spatial random fields, where each constituent component is a Matern process. The model parameters are interpretable in terms of process variance, smoothness, correlation length, and colocated correlation coefficients, which can be positive or negative. Both the marginal and the cross-covariance functions are of the Matern type. In a data example on error fields for numerical predictions of surface ...
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作者：Schwartzman, Armin
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
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作者：Tarpey, Thaddeus; Petkova, Eva; Lu, Yimeng; Govindarajulu, Usha
作者单位：University System of Ohio; Wright State University Dayton; New York University; Novartis; Novartis USA; Harvard University; Harvard University Medical Affiliates; Brigham & Women's Hospital
摘要：A longstanding problem in clinical research is distinguishing drug-treated subjects that respond due to specific effects of the drug from those that respond to nonspecific (or placebo) effects of the treatment. Linear mixed effect models are commonly used to model longitudinal clinical trial data. In this paper we present a solution to the problem of identifying placebo responders using an optimal partitioning methodology for linear mixed effects models. Since individual outcomes in a longitud...
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作者：Li, Pengfei; Chen, Jiahua
作者单位：University of Alberta; University of British Columbia
摘要：The order is an important parameter in applications of finite mixture models. Yet designing a valid and easy-to-use statistical test for the order is challenging. To date, most results on hypothesis tests have focused on homogeneity, a special case where the null model has order I. In this work, we designed an EM test for the general problem of testing the null hypothesis of order m(0) versus an alternative hypothesis of order larger than m(0). For any positive integer m(0), the null limiting ...
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作者：Cressie, Noel; Tingley, Martin P.
作者单位：University System of Ohio; Ohio State University; University System of Ohio; Ohio State University
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作者：Cai, T. Tony
作者单位：University of Pennsylvania
