Frank {RTDE} | R Documentation |
The Frank Distribution
Description
Density function, distribution function, quantile function, random generation.
Usage
dfrank(u, v, alpha, log = FALSE)
pfrank(u, v, alpha, lower.tail=TRUE, log.p = FALSE)
qfrank(p, alpha, lower.tail=TRUE, log.p = FALSE)
rfrank(n, alpha)
Arguments
u , v |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. If |
alpha |
shape parameter. |
log , log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are
|
Details
The Frank is defined by the following distribution function
C(u,v) = - \frac{1}{\alpha} \log\left[1-\frac{(1-e^{-\alpha u})(1-e^{-\alpha v}) }{ 1-e^{-\alpha}}\right],
for all u,v
in [0,1].
When lower.tail=FALSE
, pfrank
returns the survival copula
P(U > u, V > v)
.
Value
dfrank
gives the density,
pfrank
gives the distribution function,
qfrank
gives the quantile function, and
rfrank
generates random deviates.
The length of the result is determined by n
for
rfrank
, and is the maximum of the lengths of the
numerical parameters for the other functions.
The numerical parameters other than n
are recycled to the
length of the result. Only the first elements of the logical
parameters are used.
Author(s)
Christophe Dutang
References
Nelsen, R. (2006), An Introduction to Copula, Second Edition, Springer.
Examples
#####
# (1) density function
u <- v <- seq(0, 1, length=25)
cbind(u, v, dfrank(u, v, 1/2))
cbind(u, v, outer(u, v, dfrank, alpha=1/2))
#####
# (2) distribution function
cbind(u, v, pfrank(u, v, 1/2))
cbind(u, v, outer(u, v, pfrank, alpha=1/2))