SS: Spectral screening of a differential correlation matrix
In fastCorrDiff: Fast Differential Correlation Matrix Screening

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/RCode.R

The full matrix version of spectral screening method.

1	SS(D, K, K.seq = FALSE, sv = FALSE)

`D`	The difference matrix of two correlation/covariance matrices
`K`	The rank K or the maximum rank K to calculate the spectral scores
`K.seq`	logical value. If TRUE, then it returns the spectral screening scores for all rank from 1 to K. If FALSE (default), it returns the rank K result
`sv`	logical value. If TRUE, the square roots of singular values will be used in the score calculation.

This is the full version spectral screening method, which can be applicable to a few thousands of variables. If a tuning of K is needed, please use the fast.SS for tuning.

`R`	The the singular vector matrix. Each row is for one variable.
`R.sv`	The R matrix scaled by sqrt of singular values
`score`	The spectral score for screening

Tianxi Li and Xiwei Tang Maintainer: Tianxi Li tianxili@virginia.edu

Tianxi Li, Xiwei Tang, and Ajay Chatrath. Compressed spectral screening for large-scale differential correlation analysis with application in selecting Glioblastoma gene modules. arXiv preprint arXiv:2111.03721, 2021.

fast.SS

X1 <- matrix(rnorm(200),10,20)
C1 <- cor(X1)
X2 <- matrix(rnorm(200),10,20)
C2 <- cor(X2)

D <- C1-C2

fit <- SS(D, 3, K.seq = FALSE, sv = FALSE)

fit$score