permutationPA: Permutation Parallel Analysis

View source: R/find_k.R

permutationPAR Documentation

Permutation Parallel Analysis

Description

Estimate a number of significant principal components from a permutation test.

Usage

permutationPA(dat, B = 100, threshold = 0.05, verbose = TRUE)

Arguments

dat

a data matrix with m rows as variables and n columns as observations.

B

a number (a positive integer) of resampling iterations.

threshold

a numeric value between 0 and 1 to threshold p-values.

verbose

a logical indicator as to whether to print the progress.

Details

Adopted from sva::num.sv, and based on Buja and Eyuboglu (1992)

Value

permutationPA returns

r

an estimated number of significant principal components based on thresholding p-values at threshold

p

a list of p-values for significance of principal components

References

Buja A and Eyuboglu N. (1992) Remarks on parallel analysis. Multivariate Behavioral Research, 27(4), 509-540


ncchung/jackstraw documentation built on Aug. 22, 2023, 12:12 p.m.