logDet: Evaluate the log determinant

In decorrelate: Decorrelation Projection Scalable to High Dimensional Data

Evaluate the log determinant

Description

Evaluate the log determinant of the matrix

Usage

logDet(ecl, alpha = 1)

Arguments

ecl	estimate of covariance/correlation matrix from eclairs() storing U, d_1^2, \lambda and \nu
alpha	exponent to be applied to eigen-values

Value

log determinant

Examples

library(Rfast)

n <- 800 # number of samples
p <- 200 # number of features

# create correlation matrix
Sigma <- autocorr.mat(p, .9)

# draw data from correlation matrix Sigma
Y <- rmvnorm(n, rep(0, p), sigma = Sigma * 5.1, seed = 1)
rownames(Y) <- paste0("sample_", seq(n))
colnames(Y) <- paste0("gene_", seq(p))

# eclairs decomposition
ecl <- eclairs(Y)

logDet(ecl)

decorrelate documentation built on Aug. 8, 2025, 7:55 p.m.