gauss.cor: Gauss Rank Correlation Estimator
In rococo: Robust Rank Correlation Coefficient and Test

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

Compute the Gaussian rank correlation estimate

1	gauss.cor(x, y)

`x`	a numeric vector; compulsory argument
`y`	a numeric vector; compulsory argument; `x` and `y` need to have the same length

gauss.cor computes the Gaussian rank correlation estimate for x and y.

Note that gauss.cor only works for x and y being numeric vectors, unlike the classical correlation measures implemented in cor which can also be computed for matrices or data frames.

Upon successful completion, the function returns the Gaussian rank correlation estimate.

Ulrich Bodenhofer rococo@bioinf.jku.at

http://www.bioinf.jku.at/software/rococo/

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

gauss.cor.test

## create data
f <- function(x) ifelse(x > 0.9, x - 0.9, ifelse(x < -0.9, x + 0.9, 0))
x <- rnorm(25)
y <- f(x) + rnorm(25, sd=0.1)

## compute correlation
gauss.cor(x, y)