spd.dist: Distance between two symmetric, positive-definite matrices

In areshenk/spdm: Functions for working with symmetric positive-definite matrices

Distance between two symmetric, positive-definite matrices

Description

Function implements several distance measures between symmetric, positive-definite matrices.

Usage

spd.dist(x, y, method = "euclidean", ...)

Arguments

x, y	Symmetric, positive-definite matrices
method	The distance measure. See details.

Details

Allowable distance measures are

• "euclidean": The Frobenius norm of the difference x-y.

• "logeuclidean": The Frobenius norm of the difference log(x)-log(y) in the tangent space..

• "cholesky": The Frobenius norm of the difference between the cholesky factors of x and y. Not affinely invariant.

• "riemannian": The Riemmanian distance proposed by Barachant, et al. (2013)

• "stein": The square root of Jensen-Bregman log determinant divergence

areshenk/spdm documentation built on Aug. 5, 2023, 12:26 a.m.