Riemann (version 0.1.6)

wrap.euclidean: Prepare Data on Euclidean Space

Description

Euclidean space \(\mathbf{R}^p\) is the most common space for data analysis, which can be considered as a Riemannian manifold with flat metric. Since the space of matrices is isomorphic to Euclidean space after vectorization, we consider the inputs as \(p\)-dimensional vectors.

Usage

wrap.euclidean(input)

Value

a named riemdata S3 object containing

data

a list of \((p\times 1)\) matrices in \(\mathbf{R}^p\).

size

dimension of the ambient space.

name

name of the manifold of interests, "euclidean"

Arguments

input

data vectors to be wrapped as riemdata class. Following inputs are considered,

matrix

an \((n \times p)\) matrix of row observations.

list

a length-\(n\) list whose elements are length-\(p\) vectors.

Examples

#-------------------------------------------------------------------
#                 Checker for Two Types of Inputs
#
#  Generate 5 observations in R^3 in Matrix and List.
#-------------------------------------------------------------------
## DATA GENERATION
d1 = array(0,c(5,3))
d2 = list()
for (i in 1:5){
  single  = stats::rnorm(3)
  d1[i,]  = single
  d2[[i]] = single
}

## RUN
test1 = wrap.euclidean(d1)
test2 = wrap.euclidean(d2)