chi.extst {ExtremalDep}R Documentation

Tail dependence coefficient for the Extremal Skew-$t$ model

Description

Evaluates the upper and lower tail dependence coefficients for the bivariate Extremal Skew-$t$ model.

Usage

	chi.extst(corr=0, shape=rep(0,2), df=1, tail="upper")

Arguments

corr

the correlation parameter, between -1 and 1.

shape

a numeric skewness vector of length 2.

df

a single positive value representing the degree of freedom.

tail

the string "upper" or "lower".

Value

Returns a value that is strictly greater than 0 and less than 1.

Author(s)

Simone Padoan, simone.padoan@unibocconi.it, https://mypage.unibocconi.it/simonepadoan/; Boris Beranger, borisberanger@gmail.com https://www.borisberanger.com/;

References

Padoan, S. A. (2011). Multivariate extreme models based on underlying skew-t and skew-normal distributions. Journal of Multivariate Analysis, 102(5), 977-991.

Examples


### Upper tail dependence

chi.extst(corr=0.5, shape=c(1,-2), df=2, tail="upper")

### Lower tail dependence

chi.extst(corr=0.5, shape=c(1,-2), df=2, tail="lower")


[Package ExtremalDep version 0.0.3-5 Index]