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作者：Yu, Guoqiang
作者单位：Virginia Polytechnic Institute & State University
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作者：Zhao, Yunpeng
作者单位：George Mason University
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作者：Guarniero, Pieralberto; Johansen, Adam M.; Lee, Anthony
作者单位：University of Warwick
摘要：We present an offline, iterated particle filter to facilitate statistical inference in general state space hidden Markov models. Given amodel and a sequence of observations, the associated marginal likelihood L is central to likelihood-based inference for unknown statistical parameters. We define a class of twisted models: each member is specified by a sequence of positive functions. and has an associated psi-auxiliary particle filter that provides unbiased estimates of L. We identify a sequen...
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作者：Lee, Sokbae; Seo, Myung Hwan; Shin, Youngki
作者单位：Columbia University; University of London; London School Economics & Political Science; Seoul National University (SNU); University of Technology Sydney
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作者：Farjat, Alfredo; Reich, Brian J.; Guinness, Joseph; Whetten, Ross; McKeand, Steven; Isik, Fikret
作者单位：North Carolina State University; North Carolina State University
摘要：Provenance tests are a common tool in forestry designed to identify superior genotypes for planting at specific locations. The trials are replicated experiments established with seed from parent trees collected from different regions and grown at several locations. In this work, a Bayesian spatial approach is developed for modeling the expected relative performance of seed sources using climate variables as predictors associated with the origin of seed source and the planting site. The propose...
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作者：Li, Ang; Barber, Rina Foygel
作者单位：University of Chicago
摘要：Multiple testing problems arising in modern scientific applications can involve simultaneously testing thousands or even millions of hypotheses, with relatively few true signals. In this article, we consider the multiple testing problem where prior information is available (for instance, from an earlier study under different experimental conditions), that can allow us to test the hypotheses as a ranked list to increase the number of discoveries. Given an ordered list of n hypotheses, the aim i...
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作者：Wu, Guohui; Holan, Scott H.
作者单位：SAS Institute Inc; University of Missouri System; University of Missouri Columbia
摘要：Estimating abundance for multiple populations is of fundamental importance to many ecological monitoring programs. Equally important is quantifying the spatial distribution and characterizing the migratory behavior of target populations within the study domain. To achieve these goals, we propose a Bayesian hierarchical multi-population multistate Jolly-Seber model that incorporates covariates. The model is proposed using a state-space framework and-has several distinct advantages. First, multi...
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作者：Kim, Sungmin; Potter, Kevin; Craigmile, Peter F.; Peruggia, Mario; Van Zandt, Trisha
作者单位：University System of Ohio; Ohio State University; University System of Ohio; Ohio State University
摘要：Many psychological models use the idea of a trace, which represents a change in a person's cognitive state that arises as a result of processing a given stimulus. These models assume that a trace is always laid down when a stimulus is processed. In addition, some of these models explain how response times (RTs) and response accuracies arise from a process in which the different traces race against each other.In this article, we present a Bayesian hierarchical model of RT and accuracy in a diff...
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作者：Xie, Weiyi; Kurtek, Sebastian; Bharath, Karthik; Sun, Ying
作者单位：University System of Ohio; Ohio State University; University of Nottingham; King Abdullah University of Science & Technology
摘要：We propose a new method for the construction and visualization of boxplot-type displays for functional data. We use a recent functional data analysis framework, based on a representation of functions called square-root slope functions, to decompose observed variation in functional data into three main components: amplitude, phase, and vertical translation. We then construct separate displays for each component, using the geometry and metric of each representation space, based on a novel defini...
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作者：Guo, Beibei; Yuan, Ying
作者单位：Louisiana State University System; Louisiana State University; University of Texas System; UTMD Anderson Cancer Center
摘要：The optimal dose for treating patients with a molecularly targeted agent may differ according to the patient's individual characteristics, such as biomarker status. In this article, we propose a Bayesian phase I/II dose-finding design to find the optimal dose that is personalized for each patient according to his/her biomarker status. To overcome the curse of dimensionality caused by the relatively large number of biomarkers and their interactions with the dose, we employ canonical partial lea...
