rF01FrankJoe {copula} | R Documentation

## Sample Univariate Distributions Involved in Nested Frank and Joe Copulas

### Description

`rF01Frank`: Generate a vector of random variates V01 ~ F01 with Laplace-Stieltjes transform

psi01(t;V0) = ((1-(1-exp(-t)*(1-e^-theta1))^(theta0/theta1))/ (1-e^-theta0))^V0.

for the given realizations V0 of Frank's F0 and the parameters theta0, theta1 in (0,Inf) such that theta0 <= theta1. This distribution appears on sampling nested Frank copulas. The parameter `rej` is used to determine the cut-off point of two algorithms that are involved in sampling F01. If rej < V0*theta_0*(1-e^{-theta0})^(V0-1) a rejection from F01 of Joe is applied (see `rF01Joe`; the meaning of the parameter `approx` is explained below), otherwise a sum is sampled with a logarithmic envelope for each summand.

`rF01Joe`: Generate a vector of random variates V01 ~ F01 with Laplace-Stieltjes transform

psi01(t;V0) = (1-(1-exp(-t))^alpha)^V0.

for the given realizations V0 of Joe's F0 and the parameter alpha in (0,1]. This distribution appears on sampling nested Joe copulas. Here, alpha = theta0/theta1, where theta0, theta1 in [1,Inf) such that theta0 <= theta1. The parameter `approx` denotes the largest number of summands in the sum-representation of V01 before the asymptotic

V01 = V0^(1/alpha) S(alpha,1, cos^(1/alpha)(alpha*pi/2), 1_(alpha==1); 1)

is used to sample V01.

### Usage

    rF01Frank(V0, theta0, theta1, rej, approx)
    rF01Joe(V0, alpha, approx)

### Arguments

`V0` | a vector of random variates from F0.
`theta0, theta1, alpha` | parameters theta0, theta1 and alpha as described above.
`rej` | parameter value as described above.
`approx` | parameter value as described above.

### Value

A vector of positive `integer`s of length `n` containing the generated random variates.

### References

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

### See Also

`rFFrank`, `rFJoe`, `rSibuya`, and `rnacopula`.

`rnacopula`

### Examples

    ## Sample n random variates V0 ~ F0 for Frank and Joe with parameter
    ## chosen such that Kendall's tau equals 0.2 and plot histogram
    n <- 1000
    theta0.F <- copFrank@iTau(0.2)
    V0.F <- copFrank@V0(n,theta0.F)
    hist(log(V0.F), prob=TRUE); lines(density(log(V0.F)), col=2, lwd=2)
    theta0.J <- copJoe@iTau(0.2)
    V0.J <- copJoe@V0(n,theta0.J)
    hist(log(V0.J), prob=TRUE); lines(density(log(V0.J)), col=2, lwd=2)

    ## Sample corresponding V01 ~ F01 for Frank and Joe and plot histogram
    ## copFrank@V01 calls rF01Frank(V0, theta0, theta1, rej=1, approx=10000)
    ## copJoe@V01 calls rF01Joe(V0, alpha, approx=10000)
    theta1.F <- copFrank@iTau(0.5)
    V01.F <- copFrank@V01(V0.F,theta0.F,theta1.F)
    hist(log(V01.F), prob=TRUE); lines(density(log(V01.F)), col=2, lwd=2)
    theta1.J <- copJoe@iTau(0.5)
    V01.J <- copJoe@V01(V0.J,theta0.J,theta1.J)
    hist(log(V01.J), prob=TRUE); lines(density(log(V01.J)), col=2, lwd=2)

[Package copula version 0.999-15 Index]