dot-rmevA2: Multivariate extreme value distribution sampling algorithm...
In lbelzile/mev: Modelling of Extreme Values
.rmevA2 R Documentation
Multivariate extreme value distribution sampling algorithm via extremal functions
Description
Code implementing Algorithm 2 in Dombry, Engelke and Oesting (2016)
Usage
.rmevA2(n, d, par, model, Sigma, loc)
Arguments
n
sample size
d
dimension of the multivariate distribution
par
a vector of parameters
model
integer, currently ranging from 1 to 9, corresponding respectively to
(1) log, (2) neglog, (3) dirmix, (4) bilog,
(5) extstud, (6) br, (7) ct and sdir, (8) smith and (9) hr.
Sigma
covariance matrix for Brown-Resnick, Smith and extremal student. Default for compatibility
loc
matrix of location for Smith model.
Value
a n by d matrix containing the sample
lbelzile/mev documentation built on Oct. 28, 2024, 5:15 a.m.
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| .rmevA2 | R Documentation |
Multivariate extreme value distribution sampling algorithm via extremal functions
Description
Code implementing Algorithm 2 in Dombry, Engelke and Oesting (2016)
Usage
.rmevA2(n, d, par, model, Sigma, loc)
Arguments
n |
sample size |
d |
dimension of the multivariate distribution |
par |
a vector of parameters |
model |
integer, currently ranging from 1 to 9, corresponding respectively to
(1) |
Sigma |
covariance matrix for Brown-Resnick, Smith and extremal student. Default for compatibility |
loc |
matrix of location for Smith model. |
Value
a n by d matrix containing the sample
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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