log_cholesky_vec

Compute the Log-Cholesky Vectorization

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_cholesky_vec function

<dl><dt>sigma</dt>
<dd>A symmetric positive-definite matrix of class <code>dppMatrix</code></dd>
<dt>v</dt>
<dd>A symmetric matrix of class <code>dspMatrix</code></dd></dl>

Arguments

Compute the Log-Cholesky Vectorization — log_cholesky_vec

<dl>

<dt>sigma</dt>
<dd>A symmetric positive-definite matrix of class <code>dppMatrix</code></dd>


<dt>v</dt>
<dd>A symmetric matrix of class <code>dspMatrix</code></dd>

</dl>

log_cholesky_vec: Compute the Log-Cholesky Vectorization

Description

Usage

Value

Arguments