PPTvalue: Projection based Permutation Test (PPT) for canonical...

In YunhuiQi/TestPMD: Post Selection Inference on Results from Penalized Matrix Decomposition (SCCA only)

Projection based Permutation Test (PPT) for canonical correlations (singular values)

Description

This function performs Projection based Permutation Test on singular values of cross-covariance matrix between data matrices X and Y.

Usage

PPTvalue(
  X,
  Y,
  l_range,
  penalty = c("Fixed", "CV"),
  rho_x = NULL,
  rho_y = NULL,
  permutation_no
)

Arguments

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.
l_range	A vector of integers indicating which singular value to be tested.
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.

Value

A vector of p-values for singular values at position l_range.

Examples

library(TestPMD)
data("covid")
PPTvalue(X = covid$metabolite, Y = covid$protein, l_range = 1:3, penalty = "Fixed",
 rho_x = 0.9, rho_y = 0.9, permutation_no = 100)

YunhuiQi/TestPMD documentation built on May 5, 2022, 8:23 p.m.