functionaldata/tFrechet: Statistical Analysis for Random Objects and Non-Euclidean Data

Provides implementation of statistical methods for random objects lying in various metric spaces, which are not necessarily linear spaces. The core of this package is Fréchet regression for random objects with Euclidean predictors, which allows one to perform regression analysis for non-Euclidean responses under some mild conditions. Examples include distributions in L^2-Wasserstein space, covariance matrices endowed with power metric (with Frobenius metric as a special case), Cholesky and log-Cholesky metrics. References: Petersen, A., & Müller, H.-G. (2019) <doi:10.1214/17-AOS1624>.

Getting started

Package details

MaintainerYaqing Chen <yaqchen@ucdavis.edu>
LicenseBSD_3_clause + file LICENSE
Version0.2.0
URL https://github.com/functionaldata/tFrechet
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("functionaldata/tFrechet")
functionaldata/tFrechet documentation built on Oct. 12, 2024, 6:33 a.m.