# wrap.landmark: Wrap Landmark Data on Shape Space In Riemann: Learning with Data on Riemannian Manifolds

 wrap.landmark R Documentation

## Wrap Landmark Data on Shape Space

### Description

One of the frameworks used in shape space is to represent the data as landmarks. Each shape is a point set of k points in \mathbf{R}^p where each point is a labeled object. We consider general landmarks in p=2,3,…. Note that when p > 2, it is stratified space but we assume singularities do not exist or are omitted. The wrapper takes translation and scaling out from the data to make it preshape (centered, unit-norm). Also, for convenience, orthogonal Procrustes analysis is applied with the first observation being the reference so that all the other data are rotated to match the shape of the first.

### Usage

wrap.landmark(input)


### Arguments

 input data matrices to be wrapped as riemdata class. Following inputs are considered, arraya (k\times p\times n) array where each slice along 3rd dimension is a k-ad in \mathbf{R}^p. lista length-n list whose elements are k-ads.

### Value

a named riemdata S3 object containing

data

a list of preshapes in \mathbf{R}^p.

size

size of each preshape.

name

name of the manifold of interests, "landmark"

### References

\insertRef

dryden_statistical_2016Riemann

### Examples

## USE 'GORILLA' DATA
data(gorilla)
riemobj = wrap.landmark(gorilla\$male)



Riemann documentation built on March 18, 2022, 7:55 p.m.