cor2cov: Convert Correlation to Covariance Matrix

In LocaTT: Geographically-Conscious Taxonomic Assignment for Metabarcoding

Convert Correlation to Covariance Matrix

Description

Derives covariance matrix from correlation matrix and standard deviation vector.

Usage

cor2cov(sd, R)

Arguments

sd	Numeric vector of standard deviations.
R	Numeric correlation matrix.

Details

Given correlation matrix R and standard deviation vector sd, performs the operation diag(sd) %*% R %*% diag(sd) to derive the corresponding covariance matrix. This is a counterpart to stats::cov2cor, which scales a covariance matrix into the corresponding correlation matrix.

Value

Returns a numeric covariance matrix.

See Also

stats::cov2cor for scaling a covariance matrix into the corresponding correlation matrix.

Examples

# Define standard deviation vector.
sd<-c(9.655,1.157,1.128,2.925)

# Define correlation matrix.
R<-matrix(data=c(1.000,-0.80,0.64,-0.512,
                 -0.800,1.00,-0.80,0.640,
                 0.640,-0.80,1.00,-0.800,
                 -0.512,0.64,-0.80,1.000),
           ncol=4,byrow=TRUE)

# Derive covariance matrix.
cor2cov(sd=sd,R=R)

LocaTT documentation built on June 14, 2026, 1:06 a.m.