expSphere

Compute an exponential 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

expSphere function

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

Arguments

Compute an exponential map for a unit hypersphere. — expSphere

<dl>

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


<dt>tg</dt>
<dd>A vector of length \(m\) of which the exponential map is taken.</dd>

</dl>

Compute an exponential map for a unit hypersphere.

expSphere: Compute an exponential map for a unit hypersphere.

Description

Usage

Value

Arguments