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)