# K.plot: Kendall plot In lcopula: Liouville Copulas

 K.plot R Documentation

## Kendall plot

### Description

This function plots the expectation of the order statistics under the null hypothesis of independence against the ordered empirical copula values. The data is transformed to ranks.

### Usage

``````K.plot(data, add = F, ...)
``````

### Arguments

 `data` a `n` by `d` matrix of observations `add` whether to superimpose lines to an existing graph. Default to `F` `...` additional arguments passed to `points`

### Details

The function uses `integrate` and may fail for large `d` or large `n`. If `n>200`, the fallback is to generate a corresponding sample of uniform variates and to compare the empirical copula of the sample generated under the null hypothesis with the one obtained from the sample.

### Value

The Kendall plot corresponding to the data at hand

### Author(s)

Pr. Christian Genest (the code was adapted for the multivariate case)

### References

Genest & Boies (2003). Detecting Dependence with Kendall Plots, The American Statistician, 57(4), 275–284.

### Examples

``````#Independence
K.plot(matrix(runif(2000),ncol=2))
#Negative dependence
K.plot(rCopula(n=1000,claytonCopula(param=-0.5,dim=2)),add=TRUE,col=2)
#Perfect negative dependence
K.plot(rCopula(n=1000,claytonCopula(param=-1,dim=2)),add=TRUE,col=6)
#Positive dependence
K.plot(rCopula(n=1000,claytonCopula(param=iTau(claytonCopula(0.3),0.5),dim=2)),add=TRUE,col=3)
#Perfect positive dependence
K.plot(rCopula(n=1000,claytonCopula(param=iTau(claytonCopula(0.3),1),dim=2)),add=TRUE,col=4)
``````

lcopula documentation built on April 21, 2023, 9:07 a.m.