| GenPARETO {FAdist} | R Documentation |
Generalized Pareto Distribution
Description
Density, distribution function, quantile function and random generation for the generalized Pareto distribution with shape and scale parameters equal to shape and scale, respectively.
Usage
dgp(x,shape=1,scale=1,log=FALSE)
pgp(q,shape=1,scale=1,lower.tail=TRUE,log.p=FALSE)
qgp(p,shape=1,scale=1,lower.tail=TRUE,log.p=FALSE)
rgp(n,shape=1,scale=1)
Arguments
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. |
shape |
shape parameter. |
scale |
scale parameter. |
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x],otherwise, P[X > x]. |
Details
If X is a random variable distributed according to a generalized Pareto distribution, it has density
f(x) = 1/scale*(1-shape*x/scale)^((1-shape)/shape)
Value
dgp gives the density, pgp gives the distribution function, qgp gives the quantile function, and rgp generates random deviates.
References
Coles, S. (2001) An introduction to statistical modeling of extreme values. Springer
Examples
x <- rgp(1000,-.2,10)
hist(x,freq=FALSE,col='gray',border='white')
curve(dgp(x,-.2,10),add=TRUE,col='red4',lwd=2)