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 ucdavis.edu> |
| BugReports: |
https://github.com/functionaldata/tFrechet/issues |
| License: |
BSD_3_clause + file LICENSE |
| URL: |
https://github.com/functionaldata/tFrechet |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| In views: |
FunctionalData |
| CRAN checks: |
frechet results |
Documentation:
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