GPD {extraDistr} | R Documentation |
Generalized Pareto distribution
Description
Density, distribution function, quantile function and random generation for the generalized Pareto distribution.
Usage
dgpd(x, mu = 0, sigma = 1, xi = 0, log = FALSE)
pgpd(q, mu = 0, sigma = 1, xi = 0, lower.tail = TRUE, log.p = FALSE)
qgpd(p, mu = 0, sigma = 1, xi = 0, lower.tail = TRUE, log.p = FALSE)
rgpd(n, mu = 0, sigma = 1, xi = 0)
Arguments
x , q |
vector of quantiles. |
mu , sigma , xi |
location, scale, and shape parameters. Scale must be positive. |
log , log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are |
p |
vector of probabilities. |
n |
number of observations. If |
Details
Probability density function
Cumulative distribution function
Quantile function
References
Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer.
Examples
x <- rgpd(1e5, 5, 2, .1)
hist(x, 100, freq = FALSE, xlim = c(0, 50))
curve(dgpd(x, 5, 2, .1), 0, 50, col = "red", add = TRUE, n = 5000)
hist(pgpd(x, 5, 2, .1))
plot(ecdf(x))
curve(pgpd(x, 5, 2, .1), 0, 50, col = "red", lwd = 2, add = TRUE)
[Package extraDistr version 1.10.0 Index]