CPTloading | R Documentation |
This function performs Correlation based Permutation Test on singular vectors of cross-covariance matrix between data matrices X and Y (or say canonical loadings in SCCA) .
CPTloading( X, Y, side = c("X", "Y"), K, r, penalty = c("Fixed", "CV"), rho_x, rho_y, permutation_no )
X |
Data matrix, each row is one sample, each column is one feature. |
Y |
Data matrix, each row is one sample, each column is one feature. |
side |
Test singular vector with respect to X or Y, choose from "X", "Y". |
K |
The index of singular vector to be tested. |
r |
Number of components to be computed, r>=K. |
penalty |
"Fixed" or "CV": how to choose the penalty parameter, using fixed value or through cross validation. |
rho_x |
Penalty parameter used for PMD estimation of data X. If penalty = "Fixed", rho should be a single value, if penalty = "CV", rho_x should be a vector containing candidate penalty parameters for cross validation. |
rho_y |
Penalty parameter used for PMD estimation of data Y. If penalty = "Fixed", rho should be a single value, if penalty = "CV", rho_y should be a vector containing candidate penalty parameters for cross validation. |
permutation_no |
Integer: number of permutations for each test. |
A vector of p-values for K th singular vector with respect to side.
library(TestPMD) data("covid") CPTloading(X = covid$metabolite, Y = covid$protein, side = "X", K = 1, r = 10, penalty = "Fixed", rho_x = 0.5, rho_y = 0.5, permutation_no = 100)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.