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作者：He, Shiyuan; Lin, Zhenfeng; Yuan, Wenlong; Macri, Lucas M.; Huang, Jianhua Z.
作者单位：Renmin University of China; Microsoft; Johns Hopkins University; Texas A&M University System; Texas A&M University College Station; Texas A&M University System; Texas A&M University College Station
摘要：The period-luminosity relation (PLR) of Mira variable stars is an important tool to determine astronomical distances. The common approach of estimating the PLR is a two-step procedure that first estimates the Mira periods and then runs a linear regression of magnitude on log period. When the light curves are sparse and noisy, the accuracy of period estimation decreases and can suffer from aliasing effects. Some methods improve accuracy by incorporating complex model structures at the expense o...
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作者：Dai, Chenguang; Chan, Duo; Huybers, Peter; Pillai, Natesh
作者单位：Harvard University; Harvard University
摘要：Accurate estimates of historical changes in sea surface temperatures (SSTs) and their uncertainties are important for documenting and understanding historical changes in climate. A source of uncertainty that has not previously been quantified in historical SST estimates stems from position errors. A Bayesian inference framework is proposed for quantifying errors in reported positions and their implications on SST estimates. The analysis framework is applied to data from the International Compr...
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作者：Wang, Bruce; Sudijono, Timothy; Kirveslahti, Henry; Gao, Tingran; Boyer, Douglas M.; Mukherjee, Sayan; Crawford, Lorin
作者单位：Princeton University; Brown University; Duke University; University of Chicago; Duke University; Duke University; Duke University; Microsoft
摘要：The recent curation of large-scale databases with 3D surface scans of shapes has motivated the development of tools that better detect global patterns in morphological variation. Studies, which focus on identifying differences between shapes, have been limited to simple pairwise comparisons and rely on prespecified landmarks (that are often known). We present SINATRA, the first statistical pipeline for analyzing collections of shapes without requiring any correspondences. Our novel algorithm t...
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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：Benjamini, Yoav; De Veaux, Richard D.; Efron, Bradley; Evans, Scott; Glickman, Mark; Graubard, Barry, I; He, Xuming; Meng, Xiao-Li; Reid, Nancy; Stigler, Stephen M.; Vardeman, Stephen B.; Wikle, Christopher K.; Wright, Tommy; Young, Linda J.; Kafadar, Karen
作者单位：Tel Aviv University; Williams College; Stanford University; Stanford University; George Washington University; Harvard University; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); University of Michigan System; University of Michigan; University of Toronto; University of Chicago; Iowa State University; Iowa State University; University of Missouri System; University of Missouri Columbia; United States Department of Agriculture (USDA); University of Virginia
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作者：Cho, Min Ho; Kurtek, Sebastian; MacEachern, Steven N.
作者单位：University System of Ohio; Ohio State University
摘要：The classification of shapes is of great interest in diverse areas ranging from medical imaging to computer vision and beyond. While many statistical frameworks have been developed for the classification problem, most are strongly tied to early formulations of the problem with an object to be classified described as a vector in a relatively low-dimensional Euclidean space. Statistical shape data have two main properties that suggest a need for a novel approach: (i) shapes are inherently infini...
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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...
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作者：Belbahri, Mouloud; Murua, Alejandro; Gandouet, Olivier; Nia, Vahid Partovi
作者单位：Universite de Montreal; Universite de Montreal; Polytechnique Montreal
摘要：Uplift models provide a solution to the problem of isolating the marketing effect of a campaign. For customer churn reduction, uplift models are used to identify the customers who are likely to respond positively to a retention activity, only if targeted, and to avoid wasting resources on customers that are very likely to switch to another company. In practice, the uplift models performance is measured by the Qini coefficient. We introduce a Qini-based uplift regression model to analyze a larg...
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作者：McDonald, Daniel J.; McBride, Michael; Gu, Yupeng; Raphael, Christopher
作者单位：University of British Columbia; Indiana University System; Indiana University Indianapolis; Indiana University System; Indiana University Indianapolis
摘要：For concertgoers, musical interpretation is the most important factor in determining whether or not we enjoy a classical performance. Every performance includes mistakes-intonation issues, a lost note, an unpleasant sound-but these are all easily forgotten (or unnoticed) when a performer engages her audience, imbuing a piece with novel emotional content beyond the vague instructions inscribed on the printed page. In this research we use data from the CHARM Mazurka Project-46 professional recor...
