geomPCA: Geometric Principal Component Analysis

In shariq-mohammed/RADIOHEAD: Radiogenomic Analysis Incorporating Tumor Heterogeneity in Imaging Through Densities

Description

Computes the principal component (PC) scores from the geometric principal component analysis on probability density functions.

Usage

geomPCA(x, perc.var = 99, m = 512)

Arguments

x	a list with each entry as a vector of values required to compute the probability density function for that case/subject
perc.var	percentage variance explained by PCs (between 0 to 100)
m	number of equally spaced points at which the densities are to be estimated

Value

pcScores principal component scores; a matrix of size nxp, where p is the number of PCs included

Examples

x = lapply(1:10, function(i) rnorm(100))
PCScores = geomPCA(x)

shariq-mohammed/RADIOHEAD documentation built on Dec. 10, 2020, 10:19 a.m.