Abstract
Increasingly, statisticians are faced with the task of analyzing complex data that are non-Euclidean and specifically do not lie in a vector space. To address the need for statistical methods for such data, we introduce the concept of Fréchet regression. This is a general approach to regression when responses are complex random objects in a metric space and predictors are in
Citation
Alexander Petersen. Hans-Georg Müller. "Fréchet regression for random objects with Euclidean predictors." Ann. Statist. 47 (2) 691 - 719, April 2019. https://doi.org/10.1214/17-AOS1624
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