2011

最新文章

• Multi-Layer Designs for Computer Experiments AI翻译
  作者：Ba, Shan; Joseph, V. Roshan
  作者单位：University System of Georgia; Georgia Institute of Technology
  摘要：Space-filling designs such as Latin hypercube designs (LHDs) are widely used in computer experiments. However, finding an optimal LHD with good space-filling properties is computationally cumbersome. On the other hand, the well-established factorial designs in physical experiments are unsuitable for computer experiments owing to the redundancy of design points when projected onto a subset of factor space. In this work, we present a new class of space-filling designs developed by splitting two-...
• The Degrees of Freedom of Partial Least Squares Regression AI翻译
  作者：Kraemer, Nicole; Sugiyama, Masashi
  作者单位：Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics; Institute of Science Tokyo; Tokyo Institute of Technology
  摘要：The derivation of statistical properties for partial least squares regression can be a challenging task. The reason is that the construction of latent components from the predictor variables also depends on the response variable. While this typically leads to good performance and interpretable models in practice, it makes the statistical analysis more involved. In this work, we study the intrinsic complexity of partial least squares regression. Our contribution is an unbiased estimate of its d...
• Adaptive Confidence Intervals for the Test Error in Classification Comment AI翻译
  作者：Polonik, Wolfgang
  作者单位：University of California System; University of California Davis
• A Hierarchical Model for Quantifying Forest Variables Over Large Heterogeneous Landscapes With Uncertain Forest Areas AI翻译
  作者：Finley, Andrew O.; Banerjee, Sudipto; MacFarlane, David W.
  作者单位：Michigan State University; Michigan State University; University of Minnesota System; University of Minnesota Twin Cities
  摘要：We are interested in predicting one or more continuous forest variables (e.g., biomass, volume, age) at a fine resolution (e.g., pixel level) across a specified domain. Given a definition of forest/nonforest, this prediction is typically a two-step process. The first step predicts which locations are forested. The second step predicts the value of the variable for only those forested locations. Rarely is the forest/nonforest status predicted without error. However, the uncertainty in this pred...
• Model-Free Feature Screening for Ultrahigh-Dimensional Data AI翻译
  作者：Zhu, Li-Ping; Li, Lexin; Li, Runze; Zhu, Li-Xing
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Shanghai University of Finance & Economics; 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：With the recent explosion of scientific data of unprecedented size and complexity, feature ranking and screening are playing an increasingly important role in many scientific studies. In this article, we propose a novel feature screening procedure under a unified model framework, which covers a wide variety of commonly used parametric and semiparametric models. The new method does not require imposing a specific model structure on regression functions, and thus is particularly appealing to ult...
• Rao-Blackwellization for Bayesian Variable Selection and Model Averaging in Linear and Binary Regression: A Novel Data Augmentation Approach AI翻译
  作者：Ghosh, Joyee; Clyde, Merlise A.
  作者单位：University of Iowa; Duke University
  摘要：Choosing the subset of covariates to use in regression or generalized linear models is a ubiquitous problem. The Bayesian paradigm addresses the problem of model uncertainty by considering models corresponding to all possible subsets of the covariates, where the posterior distribution over models is used to select models or combine them via Bayesian model averaging (BMA). Although conceptually straightforward, BMA is often difficult to implement in practice, since either the number of covariat...
• Using Split Samples and Evidence Factors in an Observational Study of Neonatal Outcomes AI翻译
  作者：Zhang, Kai; Small, Dylan S.; Lorch, Scott; Srinivas, Sindhu; Rosenbaum, Paul R.
  作者单位：University of Pennsylvania; University of Pennsylvania
  摘要：During a few years around the turn of the millennium, a series of local hospitals in Philadelphia closed their obstetrics units, with the consequence that many mothers-to-be arrived unexpectedly at the city's large, regional teaching hospitals whose obstetrics units remained open. Nothing comparable happened in other United States cities, where there were only sporadic changes in the availability of obstetrics units. What effect did these closures have on mothers and their newborns? We study t...
• Multiple Testing for Pattern Identification, With Applications to Microarray Time-Course Experiments AI翻译
  作者：Sun, Wenguang; Wei, Zhi
  作者单位：North Carolina State University; New Jersey Institute of Technology
  摘要：In One-course experiments, it is often desirable to identify genes that exhibit a specific pattern of differential expression over time and thus gain insights into the mechanisms of the underlying biological processes. Two challenging issues in the pattern identification problem are: (i) how to combine the simultaneous inferences across multiple time points and (ii) how to control the multiplicity while accounting for the strong dependence. We formulate a compound decision-theoretic framework ...
• Modeling Three-Dimensional Chromosome Structures Using Gene Expression Data AI翻译
  作者：Xiao, Guanghua; Wang, Xinlei; Khodursky, Arkady B.
  作者单位：University of Texas System; University of Texas Southwestern Medical Center; Southern Methodist University; University of Minnesota System; University of Minnesota Twin Cities
  摘要：Recent genomic studies have shown that significant chromosomal spatial correlation exists in gene expression of many organisms. Interestingly, coexpression has been observed among genes separated by a fixed interval in specific regions of a chromosome chain, which is likely caused by three-dimensional (3D) chromosome folding structures. Modeling such spatial correlation explicitly may lead to essential understandings of 3D chromosome structures and their roles in transcriptional regulation. In...
• Dynamic Orthogonal Components for Multivariate Time Series AI翻译
  作者：Matteson, David S.; Tsay, Ruey S.
  作者单位：Cornell University; University of Chicago
  摘要：We introduce dynamic orthogonal components (DOC) for multivariate time series and propose a procedure for estimating and testing the existence of DOCs for a given time series. We estimate the dynamic orthogonal components via a generalized decorrelation method that minimizes the linear and quadratic dependence across components and across time. We then use Ljung-Box type statistics to test the existence of dynamic orthogonal components. When DOCs exist, univariate analysis can be applied to bu...