wrap.multinomial: Prepare Data on Multinomial Manifold

Description Usage Arguments Value Examples

View source: R/wrap07multinomial.R

Description

Multinomial manifold is referred to the data that is nonnegative and sums to 1. Also known as probability simplex or positive orthant, we denote (p-1) simplex in \mathbf{R}^p by

Δ^{p-1} = \lbrace x \in \mathbf{R}^p~\vert~ ∑_{i=1}^p x_i = 1, x_i > 0 \rbrace

in that data are positive L_1 unit-norm vectors. In wrap.multinomial, normalization is applied when each data point is not on the simplex, but if vectors contain values not in (0,1), it returns errors.

Usage

1

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.

Value

a named riemdata S3 object containing

data

a list of (p\times 1) matrices in Δ^{p-1}.

size

dimension of the ambient space.

name

name of the manifold of interests, "multinomial"

Examples

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#-------------------------------------------------------------------
#                 Checker for Two Types of Inputs
#-------------------------------------------------------------------
## DATA GENERATION
d1 = array(0,c(5,3))
d2 = list()
for (i in 1:5){
  single  = abs(stats::rnorm(3))
  d1[i,]  = single
  d2[[i]] = single
}

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

Riemann documentation built on June 20, 2021, 5:07 p.m.