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作者：Zhao, Yunpeng
作者单位：George Mason University
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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：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：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...
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作者：Egleston, Brian L.; Uzzo, Robert G.; Wong, Yu-Ning
作者单位：Fox Chase Cancer Center; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; Fox Chase Cancer Center; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; Fox Chase Cancer Center; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：Rates of kidney cancer have been increasing, with small incidental tumors experiencing the fastest growth rates. Much of the increase could be due to increased use of CT scans, MRIs, and ultrasounds for unrelated conditions. Many tumors might never have been detected or become symptomatic in the past. This suggests that many patients might benefit from less aggressive therapy, such as active surveillance by which tumors are surgically removed only if they become sufficiently large. However, it...
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作者：Garg, Vikram V.; Stogner, Roy H.
作者单位：Massachusetts Institute of Technology (MIT); University of Texas System; University of Texas Austin
摘要：Latin hypercube sampling (LHS) is a robust, scalable Monte Carlo method that is used in many areas of science and engineering. We present a new algorithm for generating hierarchic Latin hypercube sets (HLHS) that are recursively divisible into LHS subsets. Based on this new construction, we introduce a hierarchical incremental LHS (HILHS) method that allows the user to employ LHS in a flexibly incremental setting. This overcomes a drawback of many LHS schemes that require the entire sample set...
