BSL (version 3.0.0)

gaussianRankCorr: Gaussian rank correlation

Description

This function computes the Gaussian rank correlation of Boudt et al. (2012).

Usage

gaussianRankCorr(x, vec = FALSE)

Arguments

x

A numeric matrix representing data where the number of rows is the number of independent data points and the number of columns are the number of variables in the dataset.

vec

A logical argument indicating if the vector of correlations should be returned instead of a matrix.

Value

Gaussian rank correlation matrix (default) or a vector of pair correlations.

References

Boudt, K., Cornelissen, J., and Croux, C. (2012). The Gaussian rank correlation estimator: robustness properties. Statistics and Computing, 22(2):471-483.

See Also

cor2cov for converting a correlation matrix to a covariance matrix.

Examples

# NOT RUN {
data(ma2)
set.seed(100)

# generate 1000 simualtions from the ma2 simulation function
x <- t(replicate(1000, ma2_sim(ma2$start, 10)))

corr1 <- cor(x) # traditional correlation matrix
corr2 <- gaussianRankCorr(x) # Gaussian rank correlation matrix
par(mfrow = c(1, 2))
image(corr1, main = 'traditional correlation matrix')
image(corr2, main = 'Gaussian rank correlation matrix')

std <- apply(x, MARGIN = 2, FUN = sd) # standard deviations
cor2cov(gaussianRankCorr(x), std) # convert to covariance matrix

# }