Statistical Analysis for Random Objects and Non-Euclidean Data
Generate color bar/scale.
Generalized Fréchet integrals of covariance matrix
Fréchet mean of covariance matrices
Plots for Fréchet regression for covariance matrices.
Create density functions from raw data, histogram objects or frequency...
Fréchet ANOVA for Densities
Fréchet Change Point Detection for Densities
Fréchet means of densities.
Fréchet Variance for Densities
Distance between covariance matrices
Wasserstein distance between two distributions.
Compute an exponential map for a unit hypersphere.
Generate a "natural" frame (orthonormal basis)
frechet: Statistical Analysis for Random Objects and Non-Euclidean Dat...
Global Fréchet regression for correlation matrices
Global Fréchet regression of covariance matrices
Global density regression.
Global Cox point process regression.
Global Fréchet Regression for Spherical Data
Local Fréchet regression for correlation matrices
Local Fréchet regression of covariance matrices
Local density regression.
Local Cox point process regression.
Local Fréchet Regression for Spherical Data
Compute a log map for a unit hypersphere.
Fréchet ANOVA for Networks
Fréchet Change Point Detection for Networks
Generalized Fréchet integrals of network
Fréchet Variance for Networks
Object Covariance
Plots for Fréchet regression for univariate densities.
Transform polar to Cartesian coordinates
Geodesic distance on spheres.
Compute gradient w.r.t. y of the geodesic distance ...
Hessian of the geodesic distan...
Fréchet Variance Trajectory for densities
Generalized Fréchet integrals of 1D distribution
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 2-Wasserstein space, covariance matrices endowed with power metric (with Frobenius metric as a special case), Cholesky and log-Cholesky metrics, spherical data. References: Petersen, A., & Müller, H.-G. (2019) <doi:10.1214/17-AOS1624>.
Useful links