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作者：Wang, Zhenxun; Lin, Lifeng; Murray, Thomas; Hodges, James S.; Chu, Haitao
作者单位：University of Minnesota System; University of Minnesota Twin Cities; State University System of Florida; Florida State University
摘要：Network meta-analysis (NMA) is a powerful tool to compare multiple treatments directly and indirectly by combining and contrasting multiple independent clinical trials. Because many NMAs collect only a few eligible randomized controlled trials (RCTs), there is an urgent need to synthesize different sources of information, for example, from both RCTs and single-arm trials. However, single-arm trials and RCTs may have different populations and quality so that assuming they are exchangeable may b...
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作者：Ling, Wodan; Zhang, Wenfei; Cheng, Bin; Wei, Ying
作者单位：Fred Hutchinson Cancer Center; Sarepta Therapeutics, Inc.; Columbia University
摘要：Differential gene expression analysis based on scRNA-seq data is challenging due to two unique characteristics of scRNA-seq data. First, multimodality and other heterogeneity of the gene expression among different cell conditions lead to divergences in the tail events or crossings of the expression distributions. Second, scRNA-seq data generally have a considerable fraction of dropout events, causing zero inflation in the expression. To account for the first characteristic, existing parametric...
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作者：Jung, Sungkyu; Park, Kiho; Kim, Byungwon
作者单位：Seoul National University (SNU); Kyungpook National University (KNU)
摘要：Motivated by the analysis of torsion (dihedral) angles in the backbone of proteins, we investigate clustering of bivariate angular data on the torus [-pi, pi) x [-pi, pi). We show that naive adaptations of clustering methods, designed for vector-valued data, to the torus are not satisfactory and propose a novel clustering approach based on the conformal prediction framework. We construct several prediction sets for toroidal data with guaranteed finite-sample validity, based on a kernel density...
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作者：Franck, Christopher T.; Wilson, Christopher E.
作者单位：Virginia Polytechnic Institute & State University
摘要：Predicting the outcome of elections, sporting events, entertainment awards and other competitions has long captured the human imagination. Such prediction is growing in sophistication in these areas, especially in the rapidly growing field of data-driven journalism intended for a general audience as the availability of historical information rapidly balloons. Providing statistical methodology to probabilistically predict competition outcomes faces two main challenges. First, a suitably general...
