excess_pr_extr_mod {ExtremalDep} | R Documentation |
Exceedance Probability for bivariate or trivariate Husler-Reiss, Extremal-$t$ and Extremal Skew-$t$ models.
excess_pr_extr_mod(model, z, param)
model |
A string with the name of the model: |
z |
A vector of length |
param |
A vector containing the parameters of the model. See Details. |
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 probability.
Simone Padoan, simone.padoan@unibocconi.it, https://mypage.unibocconi.it/simonepadoan/; Boris Beranger, borisberanger@gmail.com https://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
if (interactive()){
excess_pr_extr_mod(model="hr", z=c(1,3), param=0.5)
excess_pr_extr_mod(model="hr", z=c(1,3,5), param=c(5,4,2))
excess_pr_extr_mod(model="hr", z=c(0.001,0.001,0.001), param=c(5,4,2))
}
### Extremal-t
if (interactive()){
excess_pr_extr_mod(model="Extremalt", z=c(0.1,0.3), param=c(0.5,2))
excess_pr_extr_mod(model="Extremalt", z=c(1,3,5), param=c(0.5,0.4,0.8,2))
excess_pr_extr_mod(model="Extremalt", z=c(0.001,0.001,0.001), param=c(0.5,0.4,0.8,2))
}
### Extremal Skew-t
if (interactive()){
excess_pr_extr_mod(model="Skewt", z=c(0.1,0.3), param=c(0.5,0,0,2))
excess_pr_extr_mod(model="Skewt", z=c(0.1,0.3), param=c(0.5,-10,-4,2))
excess_pr_extr_mod(model="Skewt", z=c(1,3,5), param=c(0.5,0.4,0.8,0,0,0,2))
excess_pr_extr_mod(model="Skewt", z=c(1,3,5), param=c(0.5,0.4,0.8,1,5,10,2))
excess_pr_extr_mod(model="Skewt", z=c(0.001,0.001,0.001), param=c(0.5,0.4,0.8,1,5,10,2))
}