kendall: Kendall's tau
In tranSurv: Transformation Model Based Estimation of Survival and Regression Under Dependent Truncation and Independent Censoring

Description Usage Arguments Details Value References See Also Examples

Computes the unconditional Kendall's tau

1	kendall(x, y = NULL)

`x`	a numeric vector.
`y`	a numeric vector with compatible length to `x`.

This function computes the unconditional Kendall's tau (the Kendall rank correlation coefficient) for two variables. The returned value is equivalent to that from cor with method = "kendall", but kendall is implemented in C.

The output is a numeric value for the unconditional Kendall's tau.

Kendall, M. G. (1938), A new measure of rank correlation, Biometrika, 81–93.

cor

library(MASS)
set.seed(1)
dat <- mvrnorm(5000, c(0, 0), matrix(c(1, .5, .5, 1), 2))
## True kendall's tau is 2 * asin(.5) / pi
system.time(print(kendall(dat)))
system.time(print(cor(dat, method = "kendall")))

[1] 0.3486412
   user  system elapsed 
  0.038   0.000   0.038 
          [,1]      [,2]
[1,] 1.0000000 0.3486412
[2,] 0.3486412 1.0000000
   user  system elapsed 
  1.249   0.000   1.283