log_euclidean_unvec

Converts a vector back into a tangent matrix relative to a reference point using Euclidean metric.

Implements various Riemannian metrics for symmetric positive definite matrices, including AIRM (Affine Invariant Riemannian Metric, <doi:10.1007/s11263-005-3222-z>), Log-Euclidean (<doi:10.1002/mrm.20965>), Euclidean, Log-Cholesky (<doi:10.1137/18M1221084>), and Bures-Wasserstein metrics (<doi:10.1016/j.exmath.2018.01.002>). Provides functions for computing logarithmic and exponential maps, vectorization, and statistical operations on the manifold of positive definite matrices.

Nicolas Escobar

riemtan

Riemannian Metrics for Symmetric Positive Definite Matrices

Jaroslaw Harezlak

log_euclidean_unvec function

<dl><dt>sigma</dt>
<dd>A symmetric matrix.</dd>
<dt>w</dt>
<dd>A numeric vector, representing the vectorized tangent image.</dd></dl>

Arguments

Compute the Inverse Vectorization (Euclidean) — log_euclidean_unvec

<dl>

<dt>sigma</dt>
<dd>A symmetric matrix.</dd>


<dt>w</dt>
<dd>A numeric vector, representing the vectorized tangent image.</dd>

</dl>

log_euclidean_unvec: Compute the Inverse Vectorization (Euclidean)

Description

Usage

Value

Arguments