Fréchet single index models for object response regression
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With the availability of more non-euclidean data objects, statisticians are faced with the task of developing appropriate statistical methods. For regression models in which the predictors lie in ^p and the response variables are situated in a metric space, conditional Fréchet means can be used to define the Fréchet regression function. Global and local Fréchet methods have recently been developed for modeling and estimating this regression function as extensions of multiple and local linear regression, respectively. This paper expands on these methodologies by proposing the Fréchet Single Index (FSI) model and utilizing local Fréchet along with M-estimation to estimate both the index and the underlying regression function. The method is illustrated by simulations for response objects on the surface of the unit sphere and through an analysis of human mortality data in which lifetable data are represented by distributions of age-of-death, viewed as elements of the Wasserstein space of distributions.
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