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球面到球面回归的非参数旋转方法AI 解读

Marco Di Marzioa, Agnese Panzerab & Charles C. Taylorc*a DMQTE, Università di Chieti-Pescara, Pescara, Italyb DiSIA, Università di Firenze, Firenze, Italyc Department of Statistics, University of Leeds, Leeds, UKCONTACT Charles C. Taylor charles@maths.leeds.ac.uk Department of Statistics, University of Leeds, Leeds LS2 9JT, UKSupplementary materials for this article are available online. Please go to www.tandfonline.com/r/JASA.ABSTRACTRegression of data represented as points…

球面数据的非参数回归AI 解读

We develop nonparametric smoothing for regression when both the predictor and the response variables are defined on a sphere of whatever dimension. A local polynomial fitting approach is pursued, which retains all the advantages in terms of rate optimality, interpretability, and ease of implementation widely observed in the standard setting. Our estimates have a multi-output nature, meaning that each coordinate is separately estimated, within a scheme of a regression with a…