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作者：Paige, Robert L.; Chapman, Phillip L.; Butler, Ronald W.
作者单位：University of Missouri System; Missouri University of Science & Technology; Colorado State University System; Colorado State University Fort Collins; Southern Methodist University
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作者：Ruth, David M.; Koyak, Robert A.
作者单位：United States Department of Defense; United States Navy; United States Naval Academy; United States Department of Defense; United States Navy; Naval Postgraduate School
摘要：Given a sequence of observations, has a change occurred in the underlying probability distribution with respect to observation order? This problem of detecting change points arises in a variety of applications including health prognostics for mechanical systems, syndromic disease surveillance in geographically dispersed populations, anomaly detection in information networks, and multivariate process control in general. Detecting change points in high-dimensional settings is challenging, and mo...
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作者：Jiang, Jiming; Thuan Nguyen; Rao, J. Sunil
作者单位：University of California System; University of California Davis; Oregon Health & Science University; University of Miami
摘要：We derive the best predictive estimator (BPE) of the fixed parameters under two well-known small area models, the Fay-Herriot model and the nested-error regression model. This leads to a new prediction procedure, called observed best prediction (OBP), which is different from the empirical best linear unbiased prediction (EBLUP). We show that BPE is more reasonable than the traditional estimators derived from estimation considerations, such as maximum likelihood (ML) and restricted maximum like...
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作者：Culp, Mark
作者单位：West Virginia University
摘要：This article presents a semisupervised modeling framework that combines feature-based (x) data and graph-based (G) data for classification/regression of the response Y. In this semisupervised setting, Y is observed for a subset of the observations (labeled) and missing for the remainder (unlabeled). The Propagated Scoring algorithm proposed for fitting this model is a semisupervised fixed-point regularization approach that essentially extends the generalized additive model into the semisupervi...
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作者：Nadkarni, Nivedita V.; Zhao, Yingqi; 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：An inverse regression methodology for assessing predictor performance in the censored data setup is developed along with inference procedures and a computational algorithm. The technique developed here allows for conditioning on the unobserved failure time along with a weighting mechanism that accounts for the censoring. The implementation is nonparametric and computationally fast. This provides an efficient methodological tool that can be used especially in cases where the usual modeling assu...
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作者：Chen, Lin S.; Paul, Debashis; Prentice, Ross L.; Wang, Pei
作者单位：University of Chicago; University of California System; University of California Davis; Fred Hutchinson Cancer Center
摘要：Recent proteomic studies have identified proteins related to specific phenotypes. In addition to marginal association analysis for individual proteins, analyzing pathways (functionally related sets of proteins) may yield additional valuable insights. Identifying pathways that differ between phenotypes can be conceptualized as a multivariate hypothesis testing problem: whether the mean vector mu of a p-dimensional random vector X is mu(0). Proteins within the same biological pathway may correla...
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作者：Kim, Mi-Ok; Yang, Yunwen
作者单位：Cincinnati Children's Hospital Medical Center; University of Illinois System; University of Illinois Urbana-Champaign
摘要：We consider a random effects quantile regression analysis of clustered data and propose a semiparametric approach using empirical likelihood. The random regression coefficients are assumed independent with a common mean, following parametrically specified distributions. The common mean corresponds to the population-average effects of explanatory variables on the conditional quantile of interest, whereas the random coefficients represent cluster-specific deviations in the covariate effects. We ...
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作者：Zhou, Qing
作者单位：University of California System; University of California Los Angeles
摘要：When a posterior distribution has multiple modes, unconditional expectations, such as the posterior mean, may not offer informative summaries of the distribution. Motivated by this problem, we propose to decompose the sample space of a multimodal distribution into domains of attraction of local modes. Domain-based representations are defined to summarize the probability masses of and conditional expectations on domains of attraction, which are much more informative than the mean and other unco...
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作者：Mohler, G. O.; Short, M. B.; Brantingham, P. J.; Schoenberg, F. P.; Tita, G. E.
作者单位：Santa Clara University; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles; University of California System; University of California Irvine
摘要：Highly clustered event sequences are observed in certain types of crime data, such as burglary and gang violence, due to crime-specific patterns of criminal behavior. Similar clustering patterns are observed by seismologists, as earthquakes are well known to increase the risk of subsequent earthquakes, or aftershocks, near the location of an initial event. Space time clustering is modeled in seismology by self-exciting point processes and the focus of this article is to show that these methods...
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作者：Qin, Jing; Ning, Jing; Liu, Hao; Shen, Yu
作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID); University of Texas System; UTMD Anderson Cancer Center; Baylor College of Medicine
摘要：Length-biased sampling has been well recognized in economics, industrial reliability, etiology applications, and epidemiological, genetic, and cancer screening studies. Length-biased right-censored data have a unique data structure different from traditional survival data. The nonparametric and semiparametric estimation and inference methods for traditional survival data are not directly applicable for length-biased right-censored data. We propose new expectation-maximization algorithms for es...
