pveMultiple: Percentage of Variance Explained for Multiple Data sets

In CHuanSite/SJD: Structured Joint Decomposition (SJD)

Percentage of Variance Explained for Multiple Data sets

Description

Compute the PVE (Percentage of Variance Explained) for multiple data sets on multiple components

Usage

pveMultiple(dataset, group, comp_num, list_score, list_component)

Arguments

dataset	A list of dataset to be analyzed
group	A list of grouping of the datasets, indicating the relationship between datasets
comp_num	A vector indicates the dimension of each compoent
list_score	A list of extracted scores by the corresponding algorithm
list_component	A list of components comptuted by the corresponding algorithm

Value

The list of scores

Examples

dataset = list(matrix(runif(5000, 1, 2), nrow = 100, ncol = 50),
matrix(runif(5000, 1, 2), nrow = 100, ncol = 50),
matrix(runif(5000, 1, 2), nrow = 100, ncol = 50),
matrix(runif(5000, 1, 2), nrow = 100, ncol = 50))
group = list(c(1,2,3,4), c(1,2), c(3,4), c(1,3), c(2,4), c(1), c(2), c(3), c(4))
comp_num = c(2,2,2,2,2,2,2,2,2)
res_concatPCA = concatPCA(dataset, group, comp_num)
pveMultiple(dataset, group, comp_num, res_concatPCA$score_list, res_concatPCA$linked_component_list)

CHuanSite/SJD documentation built on Nov. 29, 2024, 5:52 a.m.