SS: Spectral screening of a differential correlation matrix

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

View source: R/RCode.R

Description

The full matrix version of spectral screening method.

Usage

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

Arguments

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.

Details

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.

Value

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

Author(s)

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

References

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.

See Also

fast.SS

Examples

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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

fastCorrDiff documentation built on Nov. 18, 2021, 5:07 p.m.