Dimension Reduction for Fréchet Regression

Cites Work

Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Title not available (Why is that?)
Sufficient forecasting using factor models
Equivalence of distance-based and RKHS-based statistics in hypothesis testing
Fréchet regression for random objects with Euclidean predictors
Sufficient dimension reduction based on an ensemble of minimum average variance estimators
Tensor sliced inverse regression
On the rate of convergence in Wasserstein distance of the empirical measure
Geodesic PCA in the Wasserstein space by convex PCA
On almost linearity of low dimensional projections from high dimensional data
Successive direction extraction for estimating the central subspace in a multiple-index regres\-sion
An RKHS formulation of the inverse regression dimension-reduction problem
A characterization of spherical distributions
Regression analysis under link violation
Dimension reduction for conditional mean in regression
A general theory for nonlinear sufficient dimension reduction: formulation and estimation
Fréchet change-point detection
Nonlinear sufficient dimension reduction for functional data
Convergence and concentration of empirical measures under Wasserstein distance in unbounded functional spaces
On dimension folding of matrix- or array-valued statistical objects
On surrogate dimension reduction for measurement error regression: An invariance law
Gradient flows with metric and differentiable structures, and applications to the Wasserstein space
Contour regression: a general approach to dimension reduction
On the influence of the kernel on the consistency of support vector machines
On Directional Regression for Dimension Reduction
Sliced Inverse Regression for Dimension Reduction
On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
Nonparametric Statistical Data Modeling
Graphics for Regressions With a Binary Response
Functional sliced inverse regression analysis
Using the Bootstrap to Select One of a New Class of Dimension Reduction Methods
An Adaptive Estimation of Dimension Reduction Space
On order determination by predictor augmentation
Inverse moment methods for sufficient forecasting using high-dimensional predictors
Functional Models for Time-Varying Random Objects
Fréchet analysis of variance for random objects
An Invitation to Statistics in Wasserstein Space
Combining eigenvalues and variation of eigenvectors for order determination
Universality, Characteristic Kernels and RKHS Embedding of Measures
On Sliced Inverse Regression With High-Dimensional Covariates
Fréchet sufficient dimension reduction for random objects
Comment
Functional data analysis for density functions by transformation to a Hilbert space
Wasserstein Regression
Nonparametric Estimation and Conformal Inference of the Sufficient Forecasting With a Diverging Number of Factors