logSphere

Compute a log map for a unit hypersphere.

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>.

Yaqing Chen

frechet

Statistical Analysis for Random Objects and Non-Euclidean Data

Yidong Zhou

Han Chen

Alvaro Gajardo

Jianing Fan

Qixian Zhong

Paromita Dubey

Kyunghee Han

Satarupa Bhattacharjee

Changbo Zhu

Su I Iao

Poorbita Kundu

Petersen Alexander

Hans-Georg Müller

logSphere function

<dl><dt>base</dt>
<dd>A unit vector of length \(m\) holding the base point of the tangent space.</dd>
<dt>x</dt>
<dd>A unit vector of length \(m\) which the log map is taken.</dd></dl>

Arguments

Compute a log map for a unit hypersphere. — logSphere

<dl>

<dt>base</dt>
<dd>A unit vector of length \(m\) holding the base point of the tangent space.</dd>


<dt>x</dt>
<dd>A unit vector of length \(m\) which the log map is taken.</dd>

</dl>

Compute a log map for a unit hypersphere.

logSphere: Compute a log map for a unit hypersphere.

Description

Usage

Value

Arguments