2013

最新文章

• On Partial Sufficient Dimension Reduction With Applications to Partially Linear Multi-Index Models AI翻译
  作者：Feng, Zhenghui; Wen, Xuerong Meggie; Yu, Zhou; Zhu, Lixing
  作者单位：Xiamen University; Xiamen University; University of Missouri System; Missouri University of Science & Technology; East China Normal University; Hong Kong Baptist University
  摘要：Partial dimension reduction is a general method to seek informative convex combinations of predictors of primary interest, which includes dimension reduction as its special case when the predictors in the remaining part are constants. In this article, we propose a novel method to conduct partial dimension reduction estimation for predictors of primary interest without assuming that the remaining predictors are categorical. To this end, we first take the dichotomization step such that any exist...
• Generalized Jackknife Estimators of Weighted Average Derivatives Comment AI翻译
  作者：Dette, Holger
  作者单位：Ruhr University Bochum
• Multivariate Density Estimation by Bayesian Sequential Partitioning AI翻译
  作者：Lu, Luo; Jiang, Hui; Wong, Wing H.
  作者单位：Stanford University; University of Michigan System; University of Michigan; Stanford University
  摘要：Consider a class of densities that are piecewise constant functions over partitions of the sample space defined by sequential coordinate partitioning. We introduce a prior distribution for a density in this function class and derive in closed form the marginal posterior distribution of the corresponding partition. A computationally efficient method, based on sequential importance sampling, is presented for the inference of the partition from this posterior distribution. Compared to traditional...
• A Bayesian Reliability Analysis of Neutron-induced Errors in High Performance Computing Hardware AI翻译
  作者：Storlie, Curtis B.; Michalak, Sarah E.; Quinn, Heather M.; DuBois, Andrew J.; Wender, Steven A.; DuBois, David H.
  作者单位：United States Department of Energy (DOE); Los Alamos National Laboratory; United States Department of Energy (DOE); Los Alamos National Laboratory
  摘要：A soft error is an undesired change in an electronic device's state, for example, a bit flip in computer memory, that does not permanently affect its functionality. In microprocessor systems, neutron-induced soft errors can cause crashes and silent data corruption (SDC). SDC occurs when a soft error produces a computational result that is incorrect, without the system issuing a warning or error message. Hence, neutron-induced soft errors are a major concern for high performance computing platf...
• Case Definition and Design Sensitivity AI翻译
  作者：Small, Dylan S.; Cheng, Jing; Halloran, M. Elizabeth; Rosenbaum, Paul R.
  作者单位：University of Pennsylvania; University of California System; University of California San Francisco; Fred Hutchinson Cancer Center; University of Washington; University of Washington Seattle
  摘要：In a case-referent study, cases of disease are compared to noncases with respect to their antecedent exposure to a treatment in an effort to determine whether exposure causes some cases of the disease. Because exposure is not randomly assigned in the population, as it would be if the population were a vast randomized trial, exposed and unexposed subjects may differ prior to exposure with respect to covariates that may or may not have been measured. After controlling for measured preexposure di...
• Time-Varying Additive Models for Longitudinal Data AI翻译
  作者：Zhang, Xiaoke; Park, Byeong U.; Wang, Jane-Ling
  作者单位：University of California System; University of California Davis; Seoul National University (SNU)
  摘要：The additive model is an effective dimension-reduction approach that also provides flexibility in modeling the relation between a response variable and key covariates. The literature is largely developed to scalar response and vector covariates. In this article, more complex data are of interest, where both the response and the covariates are functions. We propose a functional additive model together with a new backfitting algorithm to estimate the unknown regression functions, whose component...
• Partially Ordered Mixed Hidden Markov Model for the Disablement Process of Older Adults AI翻译
  作者：Ip, Edward; Zhang, Qiang; Rejeski, Jack; Harris, Tammy; Kritchevsky, Stephen
  作者单位：Wake Forest University; Wake Forest University; National Institutes of Health (NIH) - USA; NIH National Institute on Aging (NIA); Wake Forest University
  摘要：At both the individual and societal levels, the health and economic burden of disability in older adults is enormous in developed countries, including the U.S. Recent studies have revealed that the disablement process in older adults often comprises episodic periods of impaired functioning and periods that are relatively free of disability, amid a secular and natural trend of decline in functioning. Rather than an irreversible, progressive event that is analogous to a chronic disease, disabili...
• Learning Sparse Causal Gaussian Networks With Experimental Intervention: Regularization and Coordinate Descent AI翻译
  作者：Fu, Fei; Zhou, Qing
  作者单位：University of California System; University of California Los Angeles
  摘要：Causal networks are graphically represented by directed acyclic graphs (DAGs). Learning causal networks from data is a challenging problem due to the size of the space of DAGs, the acyclicity constraint placed on the graphical structures, and the presence of equivalence classes. In this article, we develop an L-1-penalized likelihood approach to estimate the structure of causal Gaussian networks. A blockwise coordinate descent algorithm, which takes advantage of the acyclicity constraint, is p...
• A Bayesian Procedure for File Linking to Analyze End-of-Life Medical Costs AI翻译
  作者：Gutman, Roee; Afendulis, Christopher C.; Zaslavsky, Alan M.
  作者单位：Brown University; Harvard University; Harvard Medical School
  摘要：End-of-life medical expenses are a significant proportion of all health care expenditures. These costs were studied using costs of services from Medicare claims and cause of death (CoD) from death certificates. In the absence of a unique identifier linking the two datasets, common variables identified unique matches for only 33% of deaths. The remaining cases formed cells with multiple cases (32% in cells with an equal number of cases from each file and 35% in cells with an unequal number). We...
• Inferential Models: A Framework for Prior-Free Posterior Probabilistic Inference AI翻译
  作者：Martin, Ryan; Liu, Chuanhai
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Purdue University System; Purdue University
  摘要：Posterior probabilistic statistical inference without priors is an important but so far elusive goal. Fisher's fiducial inference, Dempster-Shafer theory of belief functions, and Bayesian inference with default priors are attempts to achieve this goal but, to date, none has given a completely satisfactory picture. This article presents a new framework for probabilistic inference, based on inferential models (IMs), which not only provides data-dependent probabilistic measures of uncertainty abo...