fastCorrDiff (version 0.5)

fastCorrDiff-package: fastCorrDiff

Description

fastCorrDiff

Details

The DESCRIPTION file: fastCorrDiff fastCorrDiff The package for fast differential correlation/covariance analysis based on spectral methods. It includes the spectral screening and compressed spectral screening methods proposed in Li et al (2021) <arXiv:2111.03721> to identify a group of variables exhibiting differential correlation pattern between two settings.The methods are designed for a great scalability when the number of variables is large, such that computing the full correlation matrices is not feasible.

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.

T. T. Cai, T. Liang, A. Rakhlin, et al. Computational and statistical boundaries for submatrix localization in a large noisy matrix. The Annals of Statistics, 45(4):1403-1430, 2017.

Examples

# NOT RUN {
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
# }