retstable: Sampling exponentially tilted stable distributions
In BayesBridge: Bridge Regression

Description Usage Arguments Value Author(s) References Examples

From the copula package:

Generating random variates of an exponentially tilted stable distribution of the form

tS(alpha, 1, (cos(alpha*pi/2)V0)^(1/alpha), V0*1_(alpha==1), h*1_(alpha!=1)),

with parameters alpha in (0,1], V0 in (0,Inf), and h in [0,Inf) and corresponding Laplace-Stieltjes transform

exp(-V0((h+t)^alpha-h^alpha)), t in [0,Inf];

see the references for more details about this distribution.

1	retstable.ld(num=1, alpha=1, V0=1, h=1)

`num`	Number of random variates to generate
`alpha`	parameter in (0,1].
`V0`	vector of values in (0,Inf) (for example, when sampling nested Clayton copulas, these are random variates from F0), that is, the distribution corresponding to psi0.
`h`	parameter in [0,Inf).

A vector of variates from tS(alpha, 1, .....); see above.

Marius Hofert, Martin Maechler

Hofert, M. (2011) Efficiently sampling nested Archimedean copulas, Computational Statistics & Data Analysis 55, 57–70.

Hofert, M. (2012), Sampling exponentially tilted stable distributions, ACM Transactions on Modeling and Computer Simulation 22, 1, page numbers: to be announced.

## Draw random variates from an exponentially tilted stable distribution
## with given alpha, V0, and h = 1
alpha <- .2
N = 200
V0 <- rgamma(N, 1)
rETS <- retstable.ld(N, alpha, V0)

## Distribution plot the random variates -- log-scaled
hist(log(rETS), prob=TRUE)
lines(density(log(rETS)), col=2)
rug (log(rETS))