frechet: 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>.

Version: 0.2.0
Imports: corrplot, fdadensity, fdapace (≥ 0.5.5), Matrix, methods, pracma, osqp
Suggests: Rcpp (≥ 0.11.5), testthat
Published: 2020-12-16
Author: Yaqing Chen [aut, cre], Alvaro Gajardo [aut], Jianing Fan [aut], Qixian Zhong [aut], Paromita Dubey [aut], Kyunghee Han [aut], Satarupa Bhattacharjee [aut], Hans-Georg Müller [cph, ths, aut]
Maintainer: Yaqing Chen <yaqchen at>
License: BSD_3_clause + file LICENSE
NeedsCompilation: no
Materials: README NEWS
In views: FunctionalData
CRAN checks: frechet results


Reference manual: frechet.pdf


Package source: frechet_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): frechet_0.2.0.tgz, r-oldrel (arm64): frechet_0.2.0.tgz, r-release (x86_64): frechet_0.2.0.tgz, r-oldrel (x86_64): frechet_0.2.0.tgz
Old sources: frechet archive


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