exponent_extr_mod {ExtremalDep} | R Documentation |
Evaluates the bivariate or trivariate exponent function of the Husler-Reiss, Extremal-$t$ and Extremal Skew-$t$ models.
exponent_extr_mod(model, z, param, dist)
model |
A string with the name of the model: |
z |
A vector of length 2 or 3, containing strictly positive reals. |
param |
A vector containing the parameters of the model. See Details. |
dist |
Logical; if |
If model="hr"
then the parameter vector is made of choose(d,2)
positive parameters, d=2,3
.
If model="Extremalt"
then the parameter vector is made of choose(d,2)
dependence parameters and a degree of freedom, d=2,3
.
If model="Skewt"
then the parameter vector is made of choose(d,2)
dependence parameters, d
shape (or skewness) parameters and a degree of freedom, d=2,3
.
Returns a single value corresponding to the exponent function or value of the distribution.
Simone Padoan, simone.padoan@unibocconi.it, http://faculty.unibocconi.it/simonepadoan; Boris Beranger, borisberanger@gmail.com http://www.borisberanger.com;
Beranger, B. and Padoan, S. A. (2015). Extreme dependence models, chapater of the book Extreme Value Modeling and Risk Analysis: Methods and Applications, Chapman Hall/CRC.
Beranger, B., Padoan, S. A. and Sisson, S. A. (2017). Models for extremal dependence derived from skew-symmetric families. Scandinavian Journal of Statistics, 44(1), 21-45.
### Husler-Reiss exponent_extr_mod(model="hr", z=c(2,3), param=1.2, dist=FALSE) exponent_extr_mod(model="hr", z=c(2,3,1), param=c(1.2,1,1.4), dist=TRUE) ### Extremal-t exponent_extr_mod(model="Extremalt", z=c(0.1,2), param=c(0.5,2), dist=FALSE) exponent_extr_mod(model="Extremalt", z=c(0.1,2,3), param=c(0.5,0.4,0.9,2), dist=TRUE) ### Extremal Skew-t exponent_extr_mod(model="Skewt", z=c(0.1,2), param=c(0.5,0,0,2), dist=FALSE) exponent_extr_mod(model="Skewt", z=c(0.1,2,3), param=c(0.5,0.4,0.9,0,0,0,2), dist=TRUE) exponent_extr_mod(model="Skewt", z=c(0.1,2,3), param=c(0.5,0.4,0.9,1,10,-5,2), dist=TRUE)