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Found 3 papers, 1 papers with code
Causal Inference on Distribution Functions
Understanding causal relationships is one of the most important goals of modern science.
Causal Inference
Methodology
Additive Models for Symmetric Positive-Definite Matrices, Riemannian Manifolds and Lie groups
The additive model for responses in the space of symmetric positive-definite matrices with either of these metrics is shown to connect to an additive model on a tangent space.
Methodology Statistics Theory Statistics Theory 62G08, 62R30
Modeling Longitudinal Data on Riemannian Manifolds
When considering functional principal component analysis for sparsely observed longitudinal data that take values on a nonlinear manifold, a major challenge is how to handle the sparse and irregular observations that are commonly encountered in longitudinal studies.
Methodology
